CN103581976B - The recognition methods of community and device - Google Patents

Abstract

The invention discloses a kind of recognition methods and device of community, method comprises: obtain user and call out corresponding call log; Abnormal information is obtained from call log; According to the anomalous event recorded in abnormal information identification call log; Community is there is according to the Sort positioning of the anomalous event identified is abnormal; The exception of preset number is selected community to occur as crucial community community from abnormal generation.By obtaining abnormal information, and according to the type of the anomalous event recorded in abnormal information identification call log, there is community according to the exception of the Sort positioning anomalous event of anomalous event, then identify crucial community accordingly in the present invention.The localization method that community occurs exception due to same class anomalous event is identical, therefore first anomalous event is classified before the abnormal generation in location community, then to anomalous event of the same type batch location, improve the recognition efficiency of crucial community, save the time, and significantly can improve accuracy of identification and the accuracy of crucial community.

Description

The recognition methods of community and device

Technical field

The present invention relates to mobile communication technology field, particularly relate to a kind of recognition methods and device of community.

Background technology

Mobile subscriber is when using communication network, often because the reasons such as poor signal quality, Internet resources deficiency cause the anomalous event such as call drop or speech quality difference in off-grid, access failure, communication process, have a strong impact on the normal use of user, and customer complaint therefore may be caused even to change operator.In order to reduce above-mentioned call abnormal problem, at present mainly through being constantly optimized communication network, but because the community forming a certain LAN is often thousands of, it is almost impossible for being optimized for each community, and usual operator is only to causing the low community of user's normal call rate to be optimized.These cause the low community of user's normal call rate to be referred to as crucial community, therefore, are effectively identify the crucial community causing user's normal call rate low to the prerequisite of network implementation optimization.

The method of the crucial community of prior art identification is: the traffic statistics index calculating all communities, carries out descending sort according to traffic statistics index to community, and the forward community of selected and sorted is crucial community.The traffic statistics index of community be the abnormal call number of times that occurs in community a period of time divided by the value of the call count gained of this community, comprise cutting off rate, access failure rate etc.Cutting off rate is the value that the abnormal call number of times that call drop occurs in a period of time community draws divided by the call count of this community, the ratio that the abnormal call number of times that call drop occurs in community during this period of time for the larger explanation of cutting off rate of community accounts for total number of calls is higher, and the call drop class of community is abnormal more serious; Access failure rate is the value that the number of calls that access failure occurs in a period of time community draws divided by the call count of this community, the ratio that the abnormal call number of times that call drop occurs in community during this period of time for the larger explanation of access failure rate of community accounts for total number of calls is higher, and the access failure class of community is abnormal more serious.

Realizing in process of the present invention, inventor finds that above-mentioned prior art at least exists following problem:

Prior art is according to the crucial community of the traffic statistics index sequencing selection of community, although can be crucial community by the cell identification of generation severely subnormal event, but can not determine that this crucial community is the community causing user's normal call rate low, namely identified crucial community and user-association poor, even if be optimized this crucial community, also effectively cannot improve the call perception of user, reduce the rate of complaints of user.

For making the problems referred to above easy to understand, now supposing that a period of time user U1 and user U2 calls out at community C1 and community C2, and processing by the carrying out of prior art to community C1, community C2, from the two, filtering out crucial community.See table 1, suppose that community C1 and community C2 phase are from not far, user U1 is everlasting movable under community C1 and community C2, and user U2 is then everlasting movable under the C2 of community.Have 10 users in a period of time community C1, user U1 is one of them, and these 10 users respectively have called 1 time and there occurs call drop in the C1 of community, and the cutting off rate calculating known community C1 is 100%.Also in the C2 of community, have called 5 times at this time period user U1 and there occurs 3 call drops, another user U2 in the C2 of community have called 5 times in this time period and there occurs 2 call drops, and the cutting off rate calculating known community C2 is 50%.

Table 1

See table 1, carry out descending sort according to prior art to community C1, community C2 according to cutting off rate, the forward community of selected and sorted is crucial community, and known C1 community is crucial community.There occurs 10 callings in the C1 of community altogether, and these 10 times callings all there occurs call drop, there occurs 10 callings in the C2 of community altogether, wherein there is call drop in 5 callings, and the call drop contrasting known community C1 is abnormal the most serious.But for user U1, this time period, user U1 have called 6 times altogether, at community C1,1 call drop occurred, and at community C2,3 call drops occurred, obviously causing the too low community of user U1 normal call rate to be community C2, is namely community C2 for the crucial community of user U1.See table 1, if operator Zhi Dui community C1 is optimized, reduce not obvious to user U1 cutting off rate obviously, namely improve not obvious to the normal call rate of user U1.

Summary of the invention

In order to solve the problem of prior art, embodiments providing a kind of recognition methods and device of community, can identify and cause the low crucial community of user's normal call rate.Described technical scheme is as follows:

First aspect, provides a kind of recognition methods of community, and described method comprises:

Obtain user and call out corresponding call log, and obtain abnormal information from described call log, described call log is the data that the carrying user obtained from communication equipment calls out behavior;

The type of the anomalous event recorded in call log according to described abnormal information identification;

Community is there is according to the Sort positioning of the anomalous event identified is abnormal;

When user's calling is the repeatedly calling of multiple user, obtain the anomalous concentration community of multiple user successively, the anomalous concentration number of users of statistics anomalous concentration community is abnormal index, by described abnormal index, ranking cells is occurred to described exception, obtain extremely sequence of cells occurring, and select the exception of preset number community to occur as crucial community sequence of cells from described abnormal generation.

In conjunction with first aspect, in the first possible implementation of first aspect, the type of the anomalous event recorded in described call log according to described abnormal information identification, comprising:

Mate described abnormal information and caller access failure or called access failure, if coupling, then identify that the type of the anomalous event recorded in described call log is for access class anomalous event.

In conjunction with first aspect, in the implementation that the second of first aspect is possible, the type of the anomalous event recorded in described call log according to described abnormal information identification, comprising:

Call drop or the on-hook of matter difference after mating described abnormal information and connecting front call drop, connect, if coupling, then identify that the type of the anomalous event recorded in described call log is for maintenance class anomalous event.

In conjunction with first aspect, in the third possible implementation of first aspect, the type of the anomalous event recorded in described call log according to described abnormal information identification, comprising:

Mate described abnormal information and up covering abnormal or descendingly covers abnormal, if coupling, then identify that the type of the anomalous event recorded in described call log is for covering class anomalous event.

In conjunction with first aspect, in the 4th kind of possible implementation of first aspect, the type of the anomalous event recorded in described call log according to described abnormal information identification, comprising:

Mate described abnormal information and uplink/downlink high-quality index HQI exception, uplink/downlink voice quality index VQI exception, uplink/downlink single-pass, uplink/downlink cross-talk or frequently switch exception, if coupling, then identify that the type of the anomalous event recorded in described call log is voice quality class anomalous event.

In conjunction with the implementation that the second of first aspect is possible, in the 5th kind of possible implementation of first aspect, the Sort positioning of the anomalous event that described basis identifies is abnormal there is community, comprising:

If the type of the anomalous event identified is access class anomalous event, then the abnormal community that occurs, location is for access community.

In conjunction with the third possible implementation of first aspect, in the 6th kind of possible implementation of first aspect, the Sort positioning of the anomalous event that described basis identifies is abnormal there is community, comprising:

If the type of the anomalous event identified keeps class anomalous event, then the abnormal community that occurs, location is for release community.

In conjunction with the 5th kind of possible implementation of first aspect, in the 7th kind of possible implementation of first aspect, the Sort positioning of the anomalous event that described basis identifies is abnormal there is community, comprising:

If the type of the anomalous event identified is uplink/downlink single-pass in voice quality class anomalous event or uplink/downlink cross-talk, then according to the log information of base station, described anomalous event place with base station controller BSC warning file location is abnormal that community occurs.

In conjunction with the third or the 4th kind of possible implementation of first aspect, in the 8th kind of possible implementation of first aspect, the Sort positioning of the anomalous event that described basis identifies is abnormal there is community, comprising:

If to be the up HQI covered in class anomalous event and/or voice quality class anomalous event abnormal and/or descending HQI is abnormal and/or up VQI is abnormal and/or descending VQI is abnormal for the type of the anomalous event identified, the abnormal measurement report MR contribution rate location of Ze An community is abnormal there is community.

In conjunction with the 8th kind of possible implementation of first aspect, in the 9th kind of possible implementation of first aspect, the described abnormal MR contribution rate location by community is abnormal there is community, comprising:

Obtain the MR record of described user calling;

Add up described user calling at the abnormal MR number N through cell i _{celli_abnormal}with the MR sum of cell i;

Calculate the abnormal MR ratio of described cell i

Judge the abnormal MR ratio of described cell i whether exceed threshold value, if exceed, then described cell i is abnormal cell, by abnormal coefficient Abnormal _cellibe set to 1; Otherwise described cell i is normal cell, by abnormal coefficient Abnormal _cellibe set to 0;

Calculate the abnormal MR contribution rate of described cell i $D_{\mathrm{Celli}\_\mathrm{abnormal}}=\frac{N_{\mathrm{Celli}\_\mathrm{abnormal}}*{\mathrm{Abnormal}}_{\mathrm{Celli}}}{\underset{i=1}{\overset{n}{\mathrm{\Σ}}}(N_{\mathrm{Celli}\_\mathrm{abnormal}}*{\mathrm{Abnormal}}_{\mathrm{Celli}})};$

According to the abnormal MR contribution rate D of community _{celli_abnormal}to described set of cells Zhong Ge community descending sort, determine extremely community to occur according to ranking results;

Wherein, described cell i is all set of cells that described user calls out process, and wherein, i is more than or equal to 1 and is less than or equal to n, described n be more than or equal to 1 integer.

In conjunction with the first possible implementation of first aspect, in the tenth kind of possible implementation of first aspect, the described abnormal abnormal index that community occurs is describedly abnormal abnormal events corresponding to community or abnormal call number or abnormal call number of users or anomalous concentration number of users occur.

In conjunction with the tenth kind of possible implementation of first aspect, in the 11 kind of possible implementation of first aspect, when described abnormal index is anomalous concentration number of users, the abnormal abnormal index that community occurs of described acquisition, comprising:

If described user's calling is the repeatedly calling of multiple user, then obtain the anomalous concentration community of described multiple user successively, the anomalous concentration number of users adding up described anomalous concentration community is abnormal index.

Second aspect, provides a kind of recognition device of community, and described device comprises:

First acquisition module, call out corresponding call log for obtaining user, described call log is the data that the carrying user obtained from communication equipment calls out behavior;

Second acquisition module, for obtaining abnormal information in the call log from described first acquisition module acquisition;

First identification module, the type of the anomalous event recorded in the call log for the first acquisition module acquisition according to the abnormal information identification of described second acquisition module acquisition;

Locating module, the Sort positioning for locating the anomalous event that described first identification module identifies is abnormal there is community;

Second identification module, for when user's calling is the repeatedly calling of multiple user, obtain the anomalous concentration community of multiple user successively, the anomalous concentration number of users of statistics anomalous concentration community is abnormal index, by described abnormal index, ranking cells is occurred to described exception, obtain extremely sequence of cells occurring, and select the exception of preset number community to occur as crucial community sequence of cells from described abnormal generation.

In conjunction with second aspect, in the first possible implementation of second aspect, described first identification module, for mating the abnormal information and caller access failure or called access failure that obtain from described second acquisition module, if coupling, then identify that the described anomalous event recorded from the call log that the first acquisition module obtains is for access class anomalous event.

In conjunction with second aspect, in the implementation that the second of second aspect is possible, described first identification module, for call drop before mating abnormal information that described second acquisition module obtains and connecting, connects after the poor on-hook of call drop or matter, if coupling, then identify that the anomalous event recorded in the call log that described first acquisition module obtains is for keeping class anomalous event.

In conjunction with second aspect; in the third possible implementation of second aspect; described first identification module; for mate described second acquisition module obtain abnormal information with up covers exception or descending cover exception; if coupling, then identify that the anomalous event recorded in the call log that described first acquisition module obtains is for covering class anomalous event.

In conjunction with second aspect, in the 4th kind of possible implementation of second aspect, described first identification module, for mating abnormal information and uplink/downlink high-quality index HQI exception, uplink/downlink voice quality index VQI exception, uplink/downlink single-pass, the uplink/downlink cross-talk of described second acquisition module acquisition or frequently switching exception, if coupling, then identify that the anomalous event recorded in the call log that described first acquisition module obtains is voice quality class anomalous event.

In conjunction with the first possible implementation of second aspect, in the 5th kind of possible implementation of second aspect, described locating module, there is community for access community in the exception for locating the access class anomalous event of described first identification module identification.

In conjunction with the implementation that the second of second aspect is possible, in the 6th kind of possible implementation of second aspect, described locating module, there is community for release community in the exception for locating the maintenance class anomalous event of described first identification module identification.

In conjunction with the third possible implementation of second aspect, in the 7th kind of possible implementation of second aspect, described locating module, for according to the log information of base station, described anomalous event place with base station controller BSC warning file location is abnormal that community occurs.

In conjunction with the second or the third possible implementation of second aspect, in the 8th kind of possible implementation of second aspect, for there is community by the abnormal measurement report MR contribution rate location of community is abnormal in described locating module.

In conjunction with the 8th kind of possible implementation of second aspect, in the 9th kind of possible implementation of second aspect, described locating module, comprising:

Acquiring unit, for obtaining the MR record of described calling;

Statistic unit, for adding up described calling at the abnormal MR number N through cell i _{celli_abnormal}with the MR sum of cell i;

First computing unit, for calculating the abnormal MR ratio of described cell i

Judging unit, for judging the abnormal MR ratio of described cell i whether exceed threshold value, if exceed, then described cell i is abnormal cell, by abnormal coefficient Abnormal _cellibe set to 1; Otherwise described cell i is normal cell, by abnormal coefficient Abnormal _cellibe set to 0;

Second computing unit, for calculating the abnormal MR contribution rate of described cell i $D_{\mathrm{Celli}\_\mathrm{abnormal}}=\frac{N_{\mathrm{Celli}\_\mathrm{abnormal}}*{\mathrm{Abnormal}}_{\mathrm{Celli}}}{\underset{i=1}{\overset{n}{\mathrm{\Σ}}}(N_{\mathrm{Celli}\_\mathrm{abnormal}}*{\mathrm{Abnormal}}_{\mathrm{Celli}})};$

Sequencing unit, for the abnormal MR contribution rate D according to community _{celli_abnormal}to described set of cells Zhong Ge community descending sort;

, extremely there is community for determining according to ranking results in determining unit;

Wherein, described cell i is all set of cells of described calling process, and wherein, i is more than or equal to 1 and is less than or equal to n, described n be more than or equal to 1 integer.

In conjunction with the first possible implementation of second aspect, in the tenth kind of possible implementation of second aspect, the abnormal index that community occurs for exception that described abnormal index acquiring unit obtains is describedly abnormal abnormal events corresponding to community or abnormal call number or abnormal call number of users or anomalous concentration number of users occur.

In conjunction with the tenth kind of possible implementation of second aspect, in the 11 kind of possible implementation of second aspect, described abnormal index acquiring unit, for when described user's calling is the repeatedly calling of multiple user, obtain the anomalous concentration community of described multiple user successively, the anomalous concentration number of users adding up described anomalous concentration community is abnormal index.

The beneficial effect that the technical scheme that the embodiment of the present invention provides is brought is:

By analyzing the abnormal information occurred in user's calling behavior, identifying the anomalous event that this abnormal information is corresponding, there is community in the exception of then locating this anomalous event place, finally selects crucial community from abnormal generation community.Because abnormal generation community is the community, immediate cause place causing user's call exception, therefore, based on the crucial community selected by abnormal generation community and user, there is relevance closely, relative to prior art, all communities are pressed to the method for the crucial community of traffic statistics index sequencing selection, the technical scheme that the embodiment of the present invention provides significantly can improve accuracy of identification and the accuracy of crucial community.

Secondly, due to the anomalous event that this abnormal information of abnormal information identification by occurring in analysis user calling behavior is corresponding, there is community in the exception of then locating this anomalous event place, finally select crucial community from abnormal generation community, therefore this user can be caused to call out the poor crucial community of impression for the specific user such as report user, VIP user rapid analysis.

Accompanying drawing explanation

In order to be illustrated more clearly in the technical scheme in the embodiment of the present invention, below the accompanying drawing used required in describing embodiment is briefly described, apparently, accompanying drawing in the following describes is only some embodiments of the present invention, for those of ordinary skill in the art, under the prerequisite not paying creative work, other accompanying drawing can also be obtained according to these accompanying drawings.

Fig. 1 is the recognition methods flow chart of a kind of community that the embodiment of the present invention one provides;

Fig. 2 is the recognition methods flow chart of a kind of community that the embodiment of the present invention two provides;

Fig. 3 is the recognition device structural representation of a kind of community that the embodiment of the present invention three provides;

Fig. 4 is the recognition device structural representation of a kind of community that the embodiment of the present invention four provides.

Embodiment

For making the object, technical solutions and advantages of the present invention clearly, below in conjunction with accompanying drawing, embodiment of the present invention is described further in detail.

In the embodiment of the present invention, calling refers to that user utilizes mobile terminal and another user to set up to converse, carry out conversing, keep the behavior of conversing or terminating to converse.Wherein, mobile terminal can include but not limited to it is mobile phone, intelligent computer or other any equipment that can carry out mobile communication.The regional classification that mobile communications network will cover is several communities, the covering radius of each community is at about 1 ~ 10km, each community set up a base station be in this cell range user service, therefore, community is the elementary cell that mobile communications network is served user, and Ye Shi operator carries out the elementary cell of the network optimization.

Embodiment one

Embodiments provide a kind of recognition methods of community, see Fig. 1, described method idiographic flow is as follows:

Step 101, obtains user and calls out corresponding call log.

In the embodiment of the present invention, call log is the data that the carrying user obtained from communication equipment calls out behavior, and communication equipment includes but not limited to mobile communication equipment, base station, base station controller, network management platform etc.Communication equipment by monitoring, to gather or the mode of storage networking corresponding interface data flow obtains and recording carrying user calls out the data of behavior.Wherein, the data that user calls out behavior include but not limited to the data relevant with user's normal call, and the data etc. when anomalous event occurs, such as call number, access code, abnormal information etc.

Step 102, obtains abnormal information from call log.

In the embodiment of the present invention, the information being used for characterizing this calling behavior outcome or process is added in call log by communication equipment for calling behavior by abnormal information, the format and content of this abnormal information can include but not limited to it is digital coding, English label, exception procedure information or other any information that can identify anomalous event, such as, the abnormal coding 10010 of caller access failure; Abnormal label: the In-Callaccessfailure of called access failure.

Step 103, according to the type of the anomalous event recorded in abnormal information identification call log.

In the embodiment of the present invention, anomalous event refers to and causes calling out the event that can not normally carry out, generally caused by non-user behavioral reasons.Residing for user the mobile network signals of environment may occur intensity or second-rate, mobile network resource is not enough or mobile network is outside there is the factors such as interference to mobile network, and these factors all may cause user to call out normally cannot carry out, namely produce anomalous event.

For the calling of the present embodiment, anomalous event may occur in moment or a moment point, also may occur in the calling procedure continued for some time, such as, caller access failure, called access failure, connect before call drop, connect after call drop, the on-hook of speech quality difference, up HQI abnormal etc.After anomalous event occurs, the abnormal information relevant with this anomalous event can be recorded in call log.

, there is community according to the Sort positioning of the anomalous event identified is abnormal in step 104, selects the exception of preset number community to occur as crucial community from abnormal generation community.

For this step, according to the anomalous event identified, judge and locate this anomalous event exception occur community.Specifically, abnormal for the abnormal or called access failure of caller access failure, its abnormal community that occurs is the access community that this is called out; For anomalous event be connect before call drop, connect after call drop or the on-hook of matter difference, it is abnormal there is the release community that community is this calling.

The abnormal community that occurs causes user can not the generation community of anomalous event of normal call, the frequency that can reduce anomalous event is optimized to any one generation in community abnormal, improve the normal call rate of user, therefore abnormal any one abnormal generation community occurred in community can as crucial community.In real operation, according to actual conditions, can select the exception of preset number that community occurs and be optimized as crucial community.

The method that the embodiment of the present invention provides, by analyzing the abnormal information occurred in user's calling behavior, identifying the anomalous event that this abnormal information is corresponding, there is community in the exception of then locating this anomalous event place, finally selects crucial community from abnormal generation community.Because abnormal generation community is the community, immediate cause place causing user's call exception, therefore, based on the crucial community selected by abnormal generation community and user, there is relevance closely, in terms of existing technologies, significantly can improve accuracy of identification and the accuracy of crucial community.

Further, based on the recognition methods of the community that the embodiment of the present invention provides, the crucial community that this user's communication can be caused to experience poor for the specific user such as report user, VIP user rapid analysis, by carrying out optimization of network performance to this crucial community in time, the abnormal problem occurred in user's communication behavior can be solved in time, the call successful rate of rapid raising user, improves user's communication impression.

Embodiment two

In conjunction with the content of above-described embodiment one, embodiments provide a kind of recognition methods of community, for convenience of explanation, the executive agent of the method that the present embodiment provides for communication equipment as the present embodiment, is illustrated the method that the present embodiment provides.See Fig. 2, method idiographic flow is as follows:

Step 201, obtains user and calls out corresponding call log.

In the embodiment of the present invention, call log is the data that the carrying user obtained from communication equipment calls out behavior, and communication equipment includes but not limited to mobile communication equipment, base station, base station controller, network management platform etc.Communication equipment by monitoring, to gather or the mode of storage networking corresponding interface data flow obtains and recording carrying user calls out the data of behavior.Wherein, the data that user calls out behavior include but not limited to the data relevant with user's normal call, and the data etc. when anomalous event occurs, such as call number, access code, abnormal information etc.

Step 202, obtains abnormal information from call log.

In the embodiment of the present invention, the information being used for characterizing this calling behavior outcome or process is added in call log by communication equipment for calling behavior by abnormal information, the format and content of this abnormal information can include but not limited to it is digital coding, English label, exception procedure information or other any information that can identify anomalous event, such as, the abnormal coding 10010 of caller access failure; Abnormal label: the In-Callaccessfailure of called access failure.By resolving call log, abnormal information can be obtained from call log.

Step 203, according to the type of the anomalous event recorded in abnormal information identification call log.

In the embodiment of the present invention, the Exception Type of anomalous event can be divided according to Different Rule, such as: the time occurred according to anomalous event can be divided into instantaneous abnormal, Process Character abnormal.

As a kind of preferred embodiment, anomalous event type comprises: access class abnormal and/or cover class abnormal and/or keep class exception and/or speech quality class abnormal.

It should be noted that, those skilled in the art can also divide anomalous event type according to custom rule when implementing of the present invention, and the embodiment of the present invention is not restricted this.

In the present embodiment, communication equipment regularly judges whether active calls exception occurs, if occur, be then recorded in the call log of active calls by the abnormal information of abnormal coding, abnormal marking or other correspondences, particular content is as follows:

1) class is accessed abnormal

Be that the abnormal or called access of caller access is abnormal if abnormal, then current exception is that access class is abnormal.Specifically: if do not receive ALERTING message after calling and non-user behavior or opposite end reason cause, then this calling behavior is caller access failure; If do not receive ALERTING message after called calling and non-user behavior or opposite end reason cause, then this calling behavior is called access failure.When meeting above condition, the abnormal information of caller/called access abnormal marking or abnormal coding or other correspondences is just recorded in corresponding call log by communication equipment.

2) keep class abnormal

Be call drop or the on-hook of matter difference after call drop before connecting, connection if abnormal, then current exception is for keeping class extremely.Specifically:

If call setup result is for " disconnectbeforeconnectacknowledge " and call setup, unsuccessfully non-user behavior is abnormal causes, then this calling behavior is call drop before connecting;

If call setup success but call out result be receive DISCONNECT message and unsuccessfully non-user behavior or opposite end reason cause, then call drop is afterwards connected in this calling behavior;

If signaling plane calls out normal termination but before channel release in N second without MR (MeasureReport, measurement report) or last M second in the uplink/downlink average quality quality of reception threshold value (such as can be set to 6 or 7 to GSM) that is greater than setting cause user cannot stand poor voice quality and initiatively on-hook, then this calling behavior is the on-hook of matter difference.

3) class is covered abnormal

Be the up calling covering abnormal or descending covering exception if abnormal, then current exception is abnormal for covering class.Specifically:

If the access level of calling is less than the up level threshold value (such as can be set to-100dBm to GSM) that the up level threshold value (such as can be set to-100dBm to GSM) of setting or average uplink incoming level are less than setting, then this calling behavior is up coverings exception;

If the average downlink reception level called out in call log is less than the downlink electrical jib door limit value (such as can be set to-90dBm to GSM) of setting, then this calling behavior is that descending covering is abnormal;

4) speech quality class is abnormal

If there is uplink/downlink high-quality index (HighQualityIndex in calling, HQI) abnormal, uplink/downlink voice quality index (VoiceQualityIndex, VQI) exception, uplink/downlink single-pass, uplink/downlink cross-talk, frequent switch abnormal etc. abnormal in any one or more exception, then be speech quality class extremely.Specifically:

If calling meets uplink/downlink receive the MR (MeasurementReport being less than or equal to " uplink/downlink high-quality thresholding " (in such as GSM, " uplink/downlink high-quality thresholding " can be set to 5), original measurement is reported) ratio is less than " the good ratio thresholding of the quality of reception " (such as can be set to 70% to GSM) of setting, then and this calling behavior is that uplink/downlink HQI is abnormal;

If the average VQI of uplink/downlink of calling is greater than " low VQI continues duration thresholding " (such as can be set to 10% to GSM) of setting lower than the ratio that " low VQI ratio thresholding " (such as can be set to 2.7 to GSM) that arrange or uplink/downlink VQI too low time account for total call duration, then this calling behavior is that uplink/downlink VOI is abnormal;

If calling has uplink/downlink single-pass record, then this calling behavior is uplink/downlink single-pass;

If calling has uplink/downlink cross-talk record, then this calling behavior is uplink/downlink cross-talk;

If calling once in call switching times exceed " the frequent switching times thresholding " of setting and average switching time interval is less than " frequent switch minimum interval thresholding " of setting, then this calling behavior is frequent switching.

For this step 203, according to the type of the anomalous event recorded in abnormal information identification call log, specifically comprise:

Coupling abnormal information and caller access failure or called access failure, if coupling, then identify that the type of the anomalous event recorded in call log is for accessing class anomalous event.

Alternatively, according to the type of the anomalous event recorded in abnormal information identification call log, specifically comprise:

Call drop or the poor on-hook of matter after mating abnormal information and connecting front call drop, connect, if coupling, then identify that the type of the anomalous event recorded in call log is keep class anomalous event.Alternatively, according to the type of the anomalous event recorded in abnormal information identification call log, specifically comprise:

Coupling abnormal information abnormal or descendingly covers abnormal with up covering, if coupling, then the type of the anomalous event recorded in identification call log is covering class anomalous event.

Alternatively, according to the type of the anomalous event recorded in abnormal information identification call log, specifically comprise:

Mate abnormal information and uplink/downlink high-quality index HQI exception, uplink/downlink voice quality index VQI exception, uplink/downlink single-pass, uplink/downlink cross-talk or frequently switch exception, if coupling, then identify that the type of the anomalous event recorded in call log is voice quality class anomalous event.

, there is community according to the Sort positioning of the anomalous event identified is abnormal in step 204.

Wherein, there is community according to the Sort positioning of the anomalous event identified is abnormal, specifically comprise:

If the type of the anomalous event identified is access class anomalous event, then the abnormal community that occurs, location is for access community.

Access community refer to caller make a call or called response calling time shared community, for mobile phone be exactly press after calling subscriber inputs called number dial to press turn-on key after key or called subscriber hear ring time mobile phone place community.

Alternatively, there is community according to the Sort positioning of the anomalous event identified is abnormal, specifically comprise:

If the type of the anomalous event identified keeps class anomalous event, then the abnormal community that occurs, location is for release community.

Community shared when release community refers to that mobile communication equipment discharges the call radio link set up with base station, for mobile phone be exactly mobile phone receive DISCONNECT message time place community.

Alternatively, there is community according to the Sort positioning of the anomalous event identified is abnormal, specifically comprise:

If the type of the anomalous event identified is uplink/downlink single-pass in voice quality class anomalous event or uplink/downlink cross-talk, then according to the log information of base station, anomalous event place with base station controller BSC warning file location is abnormal that community occurs.

Alternatively, there is community according to the Sort positioning of the anomalous event identified is abnormal, specifically comprise:

If to be the up HQI covered in class anomalous event and/or voice quality class anomalous event abnormal and/or descending HQI is abnormal and/or up VQI is abnormal and/or descending VQI is abnormal for the type of the anomalous event identified, the abnormal measurement report MR contribution rate location of Ze An community is abnormal there is community.Wherein, there is community by the abnormal MR contribution rate location of community is abnormal, specifically comprise:

Obtain the MR record of user's calling;

Statistics calling is at the abnormal MR number N through cell i _{celli_abnormal}with the MR sum of cell i;

The abnormal MR ratio of calculation plot i

Judge the abnormal MR ratio of cell i whether exceed threshold value, if exceed, then cell i is abnormal cell, by abnormal coefficient Abnormal _cellibe set to 1; Otherwise cell i is normal cell, by abnormal coefficient Abnormal _cellibe set to 0;

The abnormal MR contribution rate of calculation plot i $D_{\mathrm{Celli}\_\mathrm{abnormal}}=\frac{N_{\mathrm{Celli}\_\mathrm{abnormal}}*{\mathrm{Abnormal}}_{\mathrm{Celli}}}{\underset{i=1}{\overset{n}{\mathrm{\Σ}}}(N_{\mathrm{Celli}\_\mathrm{abnormal}}*{\mathrm{Abnormal}}_{\mathrm{Celli}})};$

According to the abnormal MR contribution rate D of community _{celli_abnormal}to set of cells Zhong Ge community descending sort, determine extremely community to occur according to ranking results;

Wherein, cell i is all set of cells that user calls out process, and wherein, i is more than or equal to 1 and is less than or equal to n, n be more than or equal to 1 integer.

If active calls occurred that up HQI is abnormal and/or descending HQI is abnormal and/or up VQI is abnormal and/or descending VQI is abnormal and/or cover abnormal in two classes or multiclass abnormal, then calculate the abnormal corresponding abnormal MR contribution rate of each class respectively, and obtain such abnormal corresponding exception generation community.Abnormal for up HQI below, the process of locating the exception generation community of up HQI exception is as follows:

Obtain the MR record of user's calling;

Statistics single call is at the up HQI abnormal MR number N through cell i _{celli_UL_HQI_abnormal}, and the MR sum of cell i;

The abnormal MR ratio of up HQI of calculation plot i

Judge the abnormal MR ratio of the up HQI of cell i whether exceed threshold value, if exceed, then cell i is up HQI abnormal cell, by abnormal coefficient Abnormal _cellibe set to 1; Otherwise cell i is non-up HQI abnormal cell, by abnormal coefficient Abnormal _cellibe set to 0;

The abnormal MR contribution rate of up HQI of calculation plot i $D_{\mathrm{Celli}\_\mathrm{UL}\_\mathrm{HQI}\_\mathrm{abnormal}}=\frac{N_{\mathrm{Celli}\_\mathrm{UL}\_\mathrm{HQI}\_\mathrm{abnormal}}*{\mathrm{Abnormal}}_{\mathrm{Celli}}}{\underset{i=1}{\overset{n}{\mathrm{\Σ}}}(N_{\mathrm{Celli}\_\mathrm{UL}\_\mathrm{HQI}\_\mathrm{abnormal}}*{\mathrm{Abnormal}}_{\mathrm{Celli}})};$

According to the abnormal MR contribution rate D of the up HQI of community _{celli_UL_HQI_abnormal}to set of cells Zhong Ge community descending sort by community, the community of getting sequence first is here the exception generation community of up HQI anomalous event;

Cell i is all set of cells that user calls out process, and wherein, i is more than or equal to 1 and is less than or equal to n, n be more than or equal to 1 integer.

Step 205, obtains the abnormal abnormal index that community occurs.

The abnormal index of this step S205 refers to and can characterize the abnormal indication information that community intensity of anomaly occurs.

Alternatively, the abnormal abnormal index that community occurs of this step S205 comprises the abnormal events or abnormal call number or abnormal call number of users or anomalous concentration number of users that generation community is corresponding extremely.

Wherein, when abnormal index is anomalous concentration number of users, obtains the abnormal abnormal index that community occurs, specifically comprise:

If user's calling is the repeatedly calling of multiple user, then obtain the anomalous concentration community of multiple user successively, the anomalous concentration number of users of statistics anomalous concentration community is abnormal index.Wherein, the anomalous concentration number of users of statistics anomalous concentration community, specifically comprises:

First community occurs by the descending sort of anomalous event number of times to the corresponding exception of repeatedly calling out of unique user, get the anomalous concentration community that front w abnormal generation community is this user, this user is called the anomalous concentration user of this w anomalous concentration community; W be greater than 1 integer; Then the anomalous concentration community of all the other users is obtained successively; The abnormal quantity that the anomalous concentration user of community occurs of statistics is anomalous concentration number of users.

, there is ranking cells by abnormal index to abnormal in step 206, obtains extremely sequence of cells occurring, and select the exception of preset number community to occur as crucial community sequence of cells from abnormal generation.

To exception, ranking cells occurring by abnormal index can be by abnormal index descending sort, also can be ascending sort, also can by other rule compositors.For descending, abnormal generation according to priority selects the exception of preset number generation community to be crucial community in sequence of cells, wherein, the priority that community occurs the exception sorting more forward is higher.

Further, for covering, the up HQI of class extremely and in voice quality class anomalous event is abnormal, descending HQI is abnormal, up VQI is abnormal and descending VQI is abnormal, due to this kind of anomalous event be in calling procedure process all communities on occur, community involved by this process may have hundreds of even thousands of, wherein, each community may be cause the above-mentioned abnormal community occurred, difference is only weighted shared by its effect causing this exception, therefore, directly the community of quantity like this is optimized as abnormal generation community and crucial community and is difficult to realize.For solving this problem, the embodiment of the present invention proposes, by the abnormal MR contribution rate location of community is abnormal, community occurs.Likely causing shared weight in above-mentioned abnormal community the highest because community occurs the exception selected by abnormal MR contribution rate, therefore, as long as select some communities, for abnormal, community occurs by abnormal MR contribution rate, each community abnormal MR contribution rate sum is made to exceed threshold value, community is there is by optimizing this exception, just can solve and cover class extremely, up/down HQI exception or up/down VQI are extremely, so, greatly reduce and need exception to be processed that number of cells occurs, make the crucial community corresponding to the exception generation community of above procedural anomalous event enter optimization and become feasible.

Further, the embodiment of the present invention adopts anomalous concentration number of users as identifying that the abnormal index of crucial community can further improve the accuracy and accuracy of identification that identify crucial community.Obtain anomalous concentration number of users to comprise: first extremely occur to select in community community that anomalous event frequency is high as anomalous concentration community multiple, then the abnormal call number of users added up in anomalous concentration community is anomalous concentration number of users.

Analyzing examples below, adopts anomalous concentration number of users as abnormal index, can improve relative to using anomalous event frequency, abnormal call number of users the precision and accuracy that identify crucial community as abnormal index:

Suppose, by identification location before, get C1, C2 and C3 tri-exceptions and community occurs, due to limited conditions, one of them can only be selected to be optimized as crucial community.These three the abnormal situations that community occurs are: there are U1 to U3 totally three users C1 community, and respectively have called ten times, wherein U1 user there occurs 9 call drops, other user's no exceptions events; There are S1 to S3 totally three users C2 community, and respectively have called ten times, each user there occurs 1 call drop; There are W1 to W3 totally three users C3 community, and respectively have called ten times, wherein W1 and W2 user respectively there occurs 4 call drops, W3 user's no exceptions event.3 abnormal there are communities and user as shown in table 2:

Table 2

Using anomalous event frequency as abnormal index, descending sort is carried out to C1, C2 and C3: C1,9 anomalous events; C3,8 anomalous events; C2,3 anomalous events.The C1 of selected and sorted first is as crucial community.

Using abnormal call number of users as abnormal index, descending sort is carried out to C1, C2 and C3: C2,3 abnormal call users; C3,2 abnormal call users; C1,1 abnormal call user.The C2 of selected and sorted first is as crucial community.

Using anomalous concentration number of users as abnormal index, descending sort is carried out to C1, C2 and C3.First selection anomalous event frequency is high C1, C3 are as anomalous concentration community, the user that anomalous event occurs at anomalous concentration community C1 or C3 is exactly anomalous concentration user, by anomalous concentration number of users, abnormal cell C1, C3 are sorted again: C3,2 anomalous concentration users; C1,1 anomalous concentration user.The C3 of selected and sorted first is as crucial community.

Table 3 is the effects after optimizing C1 community, C2 community or C3 community:

Table 3

In table 3, the summation of abnormal call number of users Shi Sange community abnormal call number of users.Cutting off rate is the comprehensive cutting off rate of C1 community, C2 community and C3 community user, computing formula: number of dropped calls/total calls * 100%.Cutting off rate is one of important indicator of branch company of examination operator of telecom operators.

By the contrast of upper table, can draw: optimize the crucial community drawn for abnormal index with anomalous event frequency, cutting off rate declines by a big margin, but abnormal user number fall is less; Optimize the crucial community drawn for abnormal index with abnormal call number of users, abnormal call number of users declines by a big margin, but cutting off rate fall is less; Optimize the crucial community drawn for abnormal index with anomalous concentration number of users, abnormal call number of users declines to a great extent, and cutting off rate also declines to a great extent simultaneously.Therefore, the embodiment of the present invention adopts anomalous concentration number of users as the crucial community of abnormal index identification, then is optimized crucial community, can obtain maximum technique effect.

, by obtaining abnormal information, and according to the type of the anomalous event recorded in abnormal information identification call log, there is community according to the exception of the Sort positioning anomalous event of anomalous event, then identifying crucial community accordingly in the method that the present embodiment provides.The localization method that community occurs exception due to same class anomalous event is identical, therefore first anomalous event is classified before the abnormal generation in location community, then to anomalous event of the same type batch location, effectively improve the recognition efficiency of crucial community, save the time.

In addition, because abnormal generation community is the community, immediate cause place causing user's call exception, therefore, based on the crucial community selected by abnormal generation community and user, there is relevance closely, in terms of existing technologies, accuracy of identification and the accuracy of crucial community can significantly be improved.

Further, based on the method that the embodiment of the present invention provides, the crucial community that this user's communication can be caused to experience poor for the specific user such as report user, VIP user rapid analysis, by carrying out optimization of network performance to this crucial community in time, the abnormal problem occurred in user's communication behavior can be solved in time, the call successful rate of rapid raising user, improves user's communication impression.

Embodiment three

Embodiments provide a kind of recognition device of community, see Fig. 3, device comprises:

First acquisition module 301, calls out corresponding call log for obtaining user;

Second acquisition module 302, for obtaining abnormal information in the call log from the first acquisition module 301 acquisition;

First identification module 303, the type of the anomalous event recorded in the call log that abnormal information identification first acquisition module for obtaining according to the second acquisition module 302 obtains;

Locating module 304, the Sort positioning for the anomalous event identified according to the first identification module 303 is abnormal there is community;

Second identification module 305, the exception for locating from locating module 304 occurs to select the exception of preset number community to occur as crucial community in community.

, by obtaining abnormal information, and according to the type of the anomalous event recorded in abnormal information identification call log, there is community according to the exception of the Sort positioning anomalous event of anomalous event, then identifying crucial community accordingly in the device that the embodiment of the present invention provides.The localization method that community occurs exception due to same class anomalous event is identical, therefore first anomalous event is classified before the abnormal generation in location community, then to anomalous event of the same type batch location, effectively improve the recognition efficiency of crucial community, save the time.

Embodiment four

Embodiments provide a kind of recognition device of community, see Fig. 4, this device comprises:

First acquisition module 401, calls out corresponding call log for obtaining user;

Second acquisition module 402, for obtaining abnormal information in the call log from the first acquisition module 401 acquisition;

First identification module 403, the type of the anomalous event recorded in the call log that abnormal information identification first acquisition module for obtaining according to the second acquisition module 402 obtains;

Locating module 404, the Sort positioning for the anomalous event identified according to the first identification module 403 is abnormal there is community;

Second identification module 405, the exception for locating from locating module 404 occurs to select the exception of preset number community to occur as crucial community in community.

As a kind of preferred embodiment, see Fig. 4, the second identification module 405, comprising:

Abnormal index acquiring unit 4051, there is the abnormal index of community in the exception of locating for obtaining locating module 404;

Crucial cell identification unit 4052, the exception generation ranking cells that the abnormal index obtained for pressing abnormal index acquiring unit 4051 is located locating module, obtain extremely sequence of cells occurring, and select the exception of preset number community to occur as crucial community sequence of cells from abnormal generation.

As a kind of preferred embodiment, first identification module 403, for mating abnormal information and the caller access failure or called access failure that the second acquisition module 402 obtains, if coupling, then identify that the anomalous event recorded in the call log that the first acquisition module obtains is for accessing class anomalous event.

Alternatively, first identification module 403, for call drop before mating abnormal information that the second acquisition module 402 obtains and connecting, connects after call drop or the on-hook of matter difference, if coupling, then identify that in the call log that the first acquisition module obtains, the anomalous event that records is maintenance class anomalous event.

Alternatively; first identification module 403; abnormal or descending covering abnormal for mating abnormal information that the second acquisition module 402 obtains with up covering, if coupling, then identifying that the anomalous event recorded in the call log of the first acquisition module acquisition is covering class anomalous event.

Alternatively, first identification module 403, for mating abnormal information and uplink/downlink high-quality index HQI exception, uplink/downlink voice quality index VQI exception, uplink/downlink single-pass, the uplink/downlink cross-talk of the second acquisition module 402 acquisition or frequently switching exception, if coupling, then identify that the anomalous event recorded in the call log that the first acquisition module obtains is voice quality class anomalous event.

As a kind of preferred embodiment, locating module 404, there is community for access community in the exception for locating the access class anomalous event that the first identification module 403 identifies.

Alternatively, locating module 404, there is community for release community in the exception for locating the maintenance class anomalous event that the first identification module 403 identifies.

Alternatively, locating module 404, for according to the log information of base station, anomalous event place with base station controller BSC warning file location is abnormal that community occurs.

Alternatively, for there is community by the abnormal measurement report MR contribution rate location of community is abnormal in locating module 404.

Further, see Fig. 4, locating module 404, specifically comprises:

Acquiring unit 4041, for obtaining the MR record of calling;

Statistic unit 4042, for adding up calling at the abnormal MR number N through cell i _{celli_abnormal}with the MR sum of cell i;

First computing unit 4043, for the abnormal MR ratio of calculation plot i

Judging unit 4044, for judging the abnormal MR ratio of cell i whether exceed threshold value, if exceed, then cell i is abnormal cell, by abnormal coefficient Abnormal _cellibe set to 1; Otherwise cell i is normal cell, by abnormal coefficient Abnormal _cellibe set to 0;

Second computing unit 4045, for the abnormal MR contribution rate of calculation plot i $D_{\mathrm{Celli}\_\mathrm{abnormal}}=\frac{N_{\mathrm{Celli}\_\mathrm{abnormal}}*{\mathrm{Abnormal}}_{\mathrm{Celli}}}{\underset{i=1}{\overset{n}{\mathrm{\Σ}}}(N_{\mathrm{Celli}\_\mathrm{abnormal}}*{\mathrm{Abnormal}}_{\mathrm{Celli}})};$

Sequencing unit 4046, for the abnormal MR contribution rate D according to community _{celli_abnormal}to set of cells Zhong Ge community descending sort;

, extremely there is community for determining according to ranking results in determining unit 4047;

Wherein, cell i be calling process all set of cells, wherein, i is more than or equal to 1 and is less than or equal to n, n be more than or equal to 1 integer.

Further, the abnormal index that community occurs the exception that abnormal index acquiring unit 4045 obtains is the abnormal events or abnormal call number or abnormal call number of users or anomalous concentration number of users that generation community is corresponding extremely.

Alternatively, abnormal index acquiring unit 4045, for when user's calling is the repeatedly calling of multiple user, obtain the anomalous concentration community of multiple user successively, the anomalous concentration number of users of statistics anomalous concentration community is abnormal index.

, by obtaining abnormal information, and according to the type of the anomalous event recorded in abnormal information identification call log, there is community according to the exception of the Sort positioning anomalous event of anomalous event, then identifying crucial community accordingly in the device that the embodiment of the present invention provides.The localization method that community occurs exception due to same class anomalous event is identical, therefore first anomalous event is classified before the abnormal generation in location community, then to anomalous event of the same type batch location, effectively improve the recognition efficiency of crucial community, save the time.

In addition, because abnormal generation community is the community, immediate cause place causing user's call exception, therefore, based on the crucial community selected by abnormal generation community and user, there is relevance closely, in terms of existing technologies, accuracy of identification and the accuracy of crucial community can significantly be improved.

Further, based on the method that the embodiment of the present invention provides, the crucial community that this user's communication can be caused to experience poor for the specific user such as report user, VIP user rapid analysis, by carrying out optimization of network performance to this crucial community in time, the abnormal problem occurred in user's communication behavior can be solved in time, the call successful rate of rapid raising user, improves user's communication impression.

Embodiment six

Present embodiments provide a kind of terminal, this terminal comprises: processor.

This processor, calls out corresponding call log for obtaining user, and obtain abnormal information from call log; According to the type of the anomalous event recorded in abnormal information identification call log; There is community according to the Sort positioning of the anomalous event identified is abnormal, select the exception of preset number community to occur as crucial community community from abnormal generation.

Further, processor selects the exception of preset number community to occur as crucial community, for obtaining the abnormal abnormal index that community occurs from abnormal generation community; There is ranking cells by abnormal index to abnormal, obtain extremely sequence of cells occurring, and select the exception of preset number community to occur as crucial community sequence of cells from abnormal generation.

Further, during the type of processor according to the anomalous event recorded in abnormal information identification call log, for mating abnormal information and caller access failure or called access failure, if coupling, then identify that the type of the anomalous event recorded in call log is for access class anomalous event.

Alternatively, during the type of processor according to the anomalous event recorded in abnormal information identification call log, for mating the front call drop of abnormal information and connection, connecting rear call drop or the on-hook of matter difference, if coupling, then the type of the anomalous event recorded in identification call log is maintenance class anomalous event.

Alternatively; during the type of processor according to the anomalous event recorded in abnormal information identification call log; for mating abnormal information and up covering abnormal or descendingly covers abnormal, if coupling, then identify that the type of the anomalous event recorded in call log is for covering class anomalous event.

Alternatively, during the type of processor according to the anomalous event recorded in abnormal information identification call log, for mating abnormal information and uplink/downlink high-quality index HQI exception, uplink/downlink voice quality index VQI exception, uplink/downlink single-pass, uplink/downlink cross-talk or frequently switching exception, if coupling, then identify that the type of the anomalous event recorded in call log is voice quality class anomalous event.

Further, when processor, according to the Sort positioning of the anomalous event identified is abnormal, community occurs, if be access class anomalous event for the type of the anomalous event identified, then the abnormal community that occurs, location is for access community.

Alternatively, when processor, according to the Sort positioning of the anomalous event identified is abnormal, community occurs, if be keep class anomalous event for the type of the anomalous event identified, then the abnormal community that occurs, location is for release community.

Alternatively, when there is community according to the Sort positioning of the anomalous event identified is abnormal in processor, if the type for the anomalous event identified is uplink/downlink single-pass in voice quality class anomalous event or uplink/downlink cross-talk, then according to the log information of base station, anomalous event place with base station controller BSC warning file location is abnormal that community occurs.

Alternatively, when there is community according to the Sort positioning of the anomalous event identified is abnormal in processor, if be that the up HQI covered in class anomalous event and/or voice quality class anomalous event is abnormal and/or descending HQI is abnormal and/or up VQI is abnormal and/or descending VQI is abnormal for the type of the anomalous event identified, the abnormal measurement report MR contribution rate location of Ze An community is abnormal there is community.

Further, when processor, by the abnormal MR contribution rate location of community is abnormal, community occurs, for obtaining the MR record of user's calling; Counting user calling is at the abnormal MR number N through cell i _{celli_abnormal}with the MR sum of cell i; The abnormal MR ratio of calculation plot i judge the abnormal MR ratio of cell i whether exceed threshold value, if exceed, then cell i is abnormal cell, by abnormal coefficient Abnormal _cellibe set to 1; Otherwise cell i is normal cell, by abnormal coefficient Abnormal _cellibe set to 0; The abnormal MR contribution rate of calculation plot i $D_{\mathrm{Celli}\_\mathrm{abnormal}}=\frac{N_{\mathrm{Celli}\_\mathrm{abnormal}}*{\mathrm{Abnormal}}_{\mathrm{Celli}}}{\underset{i=1}{\overset{n}{\mathrm{\Σ}}}(N_{\mathrm{Celli}\_\mathrm{abnormal}}*{\mathrm{Abnormal}}_{\mathrm{Celli}})};$ According to the abnormal MR contribution rate D of community _{celli_abnormal}to set of cells Zhong Ge community descending sort, determine extremely community to occur according to ranking results; Wherein, cell i is all set of cells that user calls out process, and wherein, i is more than or equal to 1 and is less than or equal to n, n be more than or equal to 1 integer.

Wherein, the abnormal abnormal index that community occurs is the abnormal events or abnormal call number or abnormal call number of users or anomalous concentration number of users that generation community is corresponding extremely.

Further, when abnormal index is anomalous concentration number of users, when this processor obtains the abnormal index of abnormal generation community, if for the repeatedly calling that user's calling is multiple user, then obtain the anomalous concentration community of multiple user successively, the anomalous concentration number of users of statistics anomalous concentration community is abnormal index.

, by obtaining abnormal information, and according to the type of the anomalous event recorded in abnormal information identification call log, there is community according to the exception of the Sort positioning anomalous event of anomalous event, then identifying crucial community accordingly in the terminal that the embodiment of the present invention provides.The localization method that community occurs exception due to same class anomalous event is identical, therefore first anomalous event is classified before the abnormal generation in location community, then to anomalous event of the same type batch location, effectively improve the recognition efficiency of crucial community, save the time.

In addition, because abnormal generation community is the community, immediate cause place causing user's call exception, therefore, based on the crucial community selected by abnormal generation community and user, there is relevance closely, in terms of existing technologies, accuracy of identification and the accuracy of crucial community can significantly be improved.

Further, based on the method that the embodiment of the present invention provides, the crucial community that this user's communication can be caused to experience poor for the specific user such as report user, VIP user rapid analysis, by carrying out optimization of network performance to this crucial community in time, the abnormal problem occurred in user's communication behavior can be solved in time, the call successful rate of rapid raising user, improves user's communication impression.

It should be noted that: the recognition device of the community that above-described embodiment provides is when identifying crucial community, only be illustrated with the division of above-mentioned each functional module, in practical application, can distribute as required and by above-mentioned functions and be completed by different functional modules, internal structure by device is divided into different functional modules, to complete all or part of function described above.In addition, the recognition device of the community that above-described embodiment provides and the recognition methods embodiment of community belong to same design, and its specific implementation process refers to embodiment of the method, repeats no more here.

The invention described above embodiment sequence number, just to describing, does not represent the quality of embodiment.

All or part of step in the embodiment of the present invention, can utilize software simulating, and corresponding software program can be stored in the storage medium that can read, as CD or hard disk etc.

The foregoing is only preferred embodiment of the present invention, not in order to limit the present invention, within the spirit and principles in the present invention all, any amendment done, equivalent replacement, improvement etc., all should be included within protection scope of the present invention.

Claims (20)

1. a recognition methods for community, is characterized in that, described method comprises:

Obtain user and call out corresponding call log, and obtain abnormal information from described call log, described call log is the data that the carrying user obtained from communication equipment calls out behavior;

The type of the anomalous event recorded in call log according to described abnormal information identification;

Community is there is according to the Sort positioning of the anomalous event identified is abnormal;

When user's calling is the repeatedly calling of multiple user, obtain the anomalous concentration community of multiple user successively, the anomalous concentration number of users of statistics anomalous concentration community is abnormal index, by described abnormal index, ranking cells is occurred to described exception, obtain extremely sequence of cells occurring, and select the exception of preset number community to occur as crucial community sequence of cells from described abnormal generation.

2. the method for claim 1, is characterized in that, the type of the anomalous event recorded in described call log according to described abnormal information identification, comprising:

Mate described abnormal information and caller access failure or called access failure, if coupling, then identify that the type of the anomalous event recorded in described call log is for access class anomalous event.

3. the method for claim 1, is characterized in that, the type of the anomalous event recorded in described call log according to described abnormal information identification, comprising:

Call drop or the on-hook of matter difference after mating described abnormal information and connecting front call drop, connect, if coupling, then identify that the type of the anomalous event recorded in described call log is for maintenance class anomalous event.

4. the method for claim 1, is characterized in that, the type of the anomalous event recorded in described call log according to described abnormal information identification, comprising:

Mate described abnormal information and up covering abnormal or descendingly covers abnormal, if coupling, then identify that the type of the anomalous event recorded in described call log is for covering class anomalous event.

5. the method for claim 1, is characterized in that, the type of the anomalous event recorded in described call log according to described abnormal information identification, comprising:

Mate described abnormal information and uplink/downlink high-quality index HQI exception, uplink/downlink voice quality index VQI exception, uplink/downlink single-pass, uplink/downlink cross-talk or frequently switch exception, if coupling, then identify that the type of the anomalous event recorded in described call log is voice quality class anomalous event.

6. method as claimed in claim 2, is characterized in that, the Sort positioning of the anomalous event that described basis identifies is abnormal, and community occurs, and comprising:

If the type of the anomalous event identified is access class anomalous event, then the abnormal community that occurs, location is for access community.

7. method as claimed in claim 3, is characterized in that, the Sort positioning of the anomalous event that described basis identifies is abnormal, and community occurs, and comprising:

If the type of the anomalous event identified keeps class anomalous event, then the abnormal community that occurs, location is for release community.

8. method as claimed in claim 5, is characterized in that, the Sort positioning of the anomalous event that described basis identifies is abnormal, and community occurs, and comprising:

If the type of the anomalous event identified is uplink/downlink single-pass in voice quality class anomalous event or uplink/downlink cross-talk, then according to the log information of base station, described anomalous event place with base station controller BSC warning file location is abnormal that community occurs.

9. the method as described in claim 4 or 5, is characterized in that, the Sort positioning of the anomalous event that described basis identifies is abnormal, and community occurs, and comprising:

If to be the up HQI covered in class anomalous event and/or voice quality class anomalous event abnormal and/or descending HQI is abnormal and/or up VQI is abnormal and/or descending VQI is abnormal for the type of the anomalous event identified, the abnormal measurement report MR contribution rate location of Ze An community is abnormal there is community.

10. method as claimed in claim 9, is characterized in that, the described abnormal MR contribution rate location by community is abnormal, and community occurs, and comprising:

Obtain the MR record of described user calling;

Add up described user calling at the abnormal MR number N through cell i _{celli_abnormal}with the MR sum of cell i;

Calculate the abnormal MR ratio of described cell i

Judge the abnormal MR ratio of described cell i whether exceed threshold value, if exceed, then described cell i is abnormal cell, by abnormal coefficient Abnormal _cellibe set to 1; Otherwise described cell i is normal cell, by abnormal coefficient Abnormal _cellibe set to 0;

Calculate the abnormal MR contribution rate of described cell i

Described cell i is all set of cells that described user calls out process, and wherein, i is more than or equal to 1 and is less than or equal to n, described n be more than or equal to 1 integer; According to the abnormal MR contribution rate D of community _{celli_abnormal}to described set of cells Zhong Ge community descending sort, determine extremely community to occur according to ranking results.

The recognition device of 11. 1 kinds of communities, is characterized in that, described device comprises:

First acquisition module, call out corresponding call log for obtaining user, described call log is the data that the carrying user obtained from communication equipment calls out behavior;

Second acquisition module, for obtaining abnormal information in the call log from described first acquisition module acquisition;

First identification module, the type of the anomalous event recorded in the call log for the first acquisition module acquisition according to the abnormal information identification of described second acquisition module acquisition;

Locating module, the Sort positioning for the anomalous event identified according to described first identification module is abnormal there is community;

Second identification module, for when user's calling is the repeatedly calling of multiple user, obtain the anomalous concentration community of multiple user successively, the anomalous concentration number of users of statistics anomalous concentration community is abnormal index, by described abnormal index, ranking cells is occurred to described exception, obtain extremely sequence of cells occurring, and select the exception of preset number community to occur as crucial community sequence of cells from described abnormal generation.

12. devices as claimed in claim 11, it is characterized in that, described first identification module, for mating the abnormal information and caller access failure or called access failure that described second acquisition module obtains, if coupling, then identify that the anomalous event recorded in the call log that described first acquisition module obtains is access class anomalous event.

13. devices as claimed in claim 11, it is characterized in that, described first identification module, for call drop before mating abnormal information that described second acquisition module obtains and connecting, connects after the poor on-hook of call drop or matter, if coupling, then identify that the anomalous event recorded in the call log that described first acquisition module obtains is for keeping class anomalous event.

14. devices as claimed in claim 11; it is characterized in that; described first identification module; for mate described second acquisition module obtain abnormal information with up covers exception or descending cover exception; if coupling, then identify that the anomalous event recorded in the call log that described first acquisition module obtains is for covering class anomalous event.

15. devices as claimed in claim 11, it is characterized in that, described first identification module, for mating abnormal information and uplink/downlink high-quality index HQI exception, uplink/downlink voice quality index VQI exception, uplink/downlink single-pass, the uplink/downlink cross-talk of described second acquisition module acquisition or frequently switching exception, if coupling, then identify that the anomalous event recorded in the call log that described first acquisition module obtains is voice quality class anomalous event.

16. devices as claimed in claim 12, is characterized in that, described locating module, and the exception for locating the access class anomalous event of described first identification module identification community occurs for access community.

17. devices as claimed in claim 13, is characterized in that, described locating module, and the exception for locating the maintenance class anomalous event of described first identification module identification community occurs for release community.

18. devices as claimed in claim 15, is characterized in that, described locating module, for according to the log information of base station, described anomalous event place with base station controller BSC warning file location is abnormal that community occurs.

19. devices as described in claims 14 or 15, is characterized in that, described locating module, for there is community by the abnormal measurement report MR contribution rate location of community is abnormal.

20. devices as claimed in claim 19, it is characterized in that, described locating module, specifically comprises:

Acquiring unit, for obtaining the MR record of described calling;

Statistic unit, for adding up described calling at the abnormal MR number N through cell i _{celli_abnormal}with the MR sum of cell i;

First computing unit, for calculating the abnormal MR ratio of described cell i

Judging unit, for judging the abnormal MR ratio of described cell i whether exceed threshold value, if exceed, then described cell i is abnormal cell, by abnormal coefficient Abnormal _cellibe set to 1; Otherwise described cell i is normal cell, by abnormal coefficient Abnormal _cellibe set to 0;

Second computing unit, for calculating the abnormal MR contribution rate of described cell i

Sequencing unit, for the abnormal MR contribution rate D according to community _{celli_abnormal}to described set of cells Zhong Ge community descending sort;

, extremely there is community for determining according to ranking results in determining unit;

Described cell i is all set of cells that described user calls out process, and wherein, i is more than or equal to 1 and is less than or equal to n, described n be more than or equal to 1 integer; According to the abnormal MR contribution rate D of community _{celli_abnormal}to described set of cells Zhong Ge community descending sort, determine extremely community to occur according to ranking results.