CN114520969A - Number card use judgment method, device, equipment and computer storage medium - Google Patents
Number card use judgment method, device, equipment and computer storage medium Download PDFInfo
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Abstract
The embodiment of the application provides a method, a device and equipment for judging number card use and a computer storage medium, wherein the method comprises the following steps: extracting all number cards to be discriminated under the same identity card; judging to obtain a main card and a non-main card according to the service information of the number card to be discriminated; and judging to obtain the card number using result according to the communication and interaction information of the main card and the non-main card. According to the number card use judgment method, the primary card and the non-primary card under the condition of one card with multiple numbers are pre-judged according to the service information of the number card, and then the use condition of the number card is accurately judged based on the communication and interaction information.
Description
Technical Field
The application belongs to the technical field of communication data analysis, and particularly relates to a method, a device, equipment and a computer storage medium for number card use judgment.
Background
With the continuous development of operator services, card number resources cannot actually represent real user resources. The current operation mode taking the card number as the center is difficult to accurately evaluate the value and the demand of the customer, and marketing resources cannot be accurately released.
The same natural person has a plurality of telephone numbers, the user uses the personal identification card to handle a plurality of number cards, the use condition is complex, the number cards can be given to relatives for use, placed in another mobile phone or idle in an intelligent terminal and the like, and the accurate positioning and analysis of the user by an operator are not facilitated. At present, the mode of identifying whether a plurality of mobile phone numbers belong to the same natural person mainly utilizes identity card registration information, and the problem of low identification accuracy exists.
Therefore, how to accurately identify the condition of the subscriber number card is a technical problem to be solved by the technical personnel in the field.
Disclosure of Invention
The embodiment of the application provides a number card use judgment method, a number card use judgment device and a computer storage medium, wherein the number card under the existing identity card can be classified according to daily business rules, and the use condition of the number card is accurately judged by combining the user call similarity and the activity track base station contact ratio so as to realize the accurate marketing of one-line personnel in the market to a plurality of number card users and save the resource investment.
In a first aspect, an embodiment of the present application provides a method for determining number card usage, where the method includes:
extracting all number cards to be discriminated under the same identity card;
judging to obtain a main card and a non-main card according to the service information of the number card to be discriminated;
and judging to obtain the card number using result according to the communication information of the main card and the non-main card.
Further, according to the service information of the number card to be discriminated, the method for judging and obtaining the main card comprises the following steps:
judging the main package cost, ARPU (average every 3 months), DOU (average every 3 months) and MOU (average every 3 months), wherein the highest card is the main card;
and judging that the number card transacted with the business needing to be transacted by the user is the main card.
Further, according to the service information of the number card to be discriminated, the method for judging and obtaining the non-main card comprises the following steps:
if the number card to be discriminated is in the multi-card terminal and the number card with the registration time earlier than that of the number card to be discriminated exists, the number card to be discriminated is judged to be a non-primary card;
and judging whether the calling card and the called card generate calling and called calls with the main card, wherein the number card with the average call duration larger than the preset call duration is a non-main card.
Further, the judging and obtaining the card number using result according to the communication and interaction information between the main card and the non-main card comprises:
if the proportion of the non-answering behavior in the conversation behaviors of the main card and the non-main card is larger than a preset non-answering threshold, judging that the main card and the non-main card are used by the same person;
and if the same proportion of the numbers of the opposite terminals dialed by the user is greater than a preset opposite terminal dialing threshold value, judging that the main card and the non-main card are used by the same person.
Further, the judging and obtaining the card number using result according to the communication and interaction information between the main card and the non-main card comprises:
acquiring data of base stations where a main card and a non-main card are located;
sequencing according to the occurrence frequency of the base station, and respectively generating a frequent item set base station sequence list;
calculating a first contact ratio of a frequent item set of a base station where a main card and a non-main card are located;
and if the first contact ratio is greater than the preset movable contact ratio threshold value, judging that the main card and the non-main card are used by the same person.
Further, still include: respectively screening out resident base stations of the main card and the non-main card within a preset time period;
judging the second overlapping degree of the base station where the main card and the non-main card are positioned in the same time slot;
and if the second coincidence degree is larger than the preset dwell coincidence degree threshold value, judging that the main card and the non-main card are used by the same person.
Further, according to the communication information of the main card and the non-main card, the method for judging and obtaining the card number using result includes:
screening a data set to be tested consisting of the number cards to be discriminated;
obtaining a non-main card user sample in a main card, and obtaining a model positive sample; obtaining a non-main card user sample in a non-main card, and obtaining a model negative sample;
respectively calculating the call similarity between the model positive sample and the model negative sample and the main card and the contact ratio between the active track base station and the active track base station;
establishing a number card recognition neural network model based on the call similarity and the overlap ratio of the moving track base station;
processing a data set of a number card to be discriminated by using a number card recognition neural network model to obtain a self-use probability vector;
and judging to obtain the card number use result according to the self-use probability vector.
Further, respectively calculating the call similarity between the model positive sample and the model negative sample and the master card and the contact ratio between the model positive sample and the model negative sample and the master card, including:
and calculating the contact ratio of the base station of the moving track by using an FP-Growth algorithm.
Further, still include:
adding category identification vectors in a data set to be measured to obtain a prediction data set; if the number card to be discriminated is the same terminal number card as the main card, the category identification vector is 1; if not, the category identification vector is 0;
establishing a confusion matrix according to the prediction data set and the self-use probability vector;
and obtaining the accuracy, the recall rate and the accuracy of the using result of the number card according to the confusion matrix.
In a second aspect, an embodiment of the present application provides a number card use determination apparatus, including:
the data acquisition module is used for extracting all the number cards to be discriminated under the same identity card;
the business rule judging module is used for judging to obtain a main card and a non-main card according to the business information of the number card to be discriminated;
and the result judging module is used for judging and obtaining the card number using result according to the communication and interaction information of the main card and the non-main card.
Further, the result judgment module comprises:
the conversation similarity characteristic module is used for judging whether the main card and the non-main card are used by the same person or not according to the communication and interaction information of the main card and the non-main card;
and the mobile track base station contact ratio calculation module is used for judging whether the main card and the non-main card are used by the same person or not according to the contact ratio of the information of the base stations of the main card and the non-main card.
Further, still include:
the characteristic integration model processing module is used for calculating a main card probability vector of the use probability of the main card and the non-main card for the same person according to the data output by the call similarity characteristic module and the activity track base station contact ratio calculating module;
and the effect verification module is used for obtaining the accuracy rate, the recall rate and the accuracy rate of the card number using result according to the card probability vector of the user.
In a third aspect, an embodiment of the present application provides a number card use determination device, where the device includes:
a processor, and a memory storing computer program instructions; the processor reads and executes the computer program instructions to realize the card number use judgment method.
In a fourth aspect, an embodiment of the present application provides a computer storage medium, where computer program instructions are stored on the computer storage medium, and when the computer program instructions are executed by a processor, the method for determining number card usage as described above is implemented.
The number card use judgment method, device, equipment and computer storage medium in the embodiment of the application can pre-judge the primary card and the non-primary card under the condition of one card with multiple numbers according to the service information of the number card, and then realize accurate judgment of the use condition of the number card based on the communication and interaction information.
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In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required to be used in the embodiments of the present application will be briefly described below, and for those skilled in the art, other drawings may be obtained according to the drawings without creative efforts.
Fig. 1 is a schematic flowchart of a method for determining card number usage according to an embodiment of the present application;
fig. 2 is a schematic diagram illustrating a method for calculating number card call similarity in a number card usage determination method according to an embodiment of the present application;
fig. 3 is a diagram illustrating a prefix tree generated based on a base station sequence table in a number card usage determination method according to an embodiment of the present application;
fig. 4 is a flowchart of a method for determining number card usage according to an embodiment of the present application;
fig. 5 is a schematic structural diagram of a number card use determination device according to an embodiment of the present application;
fig. 6 is a schematic structural diagram of a number card use judgment device according to an embodiment of the present application.
Detailed Description
Features and exemplary embodiments of various aspects of the present application will be described in detail below, and in order to make objects, technical solutions and advantages of the present application more apparent, the present application will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are intended to be illustrative only and are not intended to be limiting. It will be apparent to one skilled in the art that the present application may be practiced without some of these specific details. The following description of the embodiments is merely intended to provide a better understanding of the present application by illustrating examples thereof.
It should be noted that, in this document, relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
The prior art scheme is mostly applied to the fields of public security, banks and the like in the aspect of identification of the same person, is less related to the field of operators, and is less in the use and identification method of the natural person number card for one-card multi-card users. In the aspect of similarity evaluation between user number cards, the prior technical scheme has no further multi-dimensional mining on call behavior and position characteristics, does not combine the determined number card relation information and the condition of business rule prejudgment for identification, and has a single rough judgment mode.
In order to solve the prior art problems, embodiments of the present application provide a method, an apparatus, a device and a computer storage medium for determining number card usage, so as to achieve determination of a number card usage situation of a natural person who faces a one-card multi-card user.
The technical scheme is that the natural person identification method based on the call similarity and the activity track classifies the number cards under the existing identity cards by combining the call similarity of users and the contact ratio of the activity track base station through daily business rules, accurately judges the use condition of the number cards of the users with one card and multiple cards, and is beneficial to the accurate marketing of one-line staff in the market to the users with multiple cards so as to save the resource investment.
First, a method for using a one-card multi-card user number card provided in the embodiment of the present application is described below.
Fig. 1 is a schematic flowchart illustrating a method for determining number card usage according to an embodiment of the present application. As shown in fig. 1, the method may include the steps of:
s1: extracting all number cards to be discriminated under the same identity card;
extracting mobile phone number cards under the same identity card, namely number cards to be discriminated, according to mobile phone number information registered by an operator; the using condition of the number card to be discriminated is judged, and whether the number card is used by the same person or not is mainly judged.
S2: judging to obtain a main card and a non-main card according to the service information of the number card to be discriminated;
generally, if the cards are used by the same person, the package charge of the main card is higher, and the package quantity is larger; therefore, the service condition of the number card can be preliminarily estimated according to the operation business information of the number card, and the primary card and the non-primary card can be preliminarily judged.
S3: and judging to obtain the card number using result according to the communication information of the main card and the non-main card.
The use condition of the number card to be discriminated can be obtained by judging the obtained main card and the non-main card based on the mobile phone service information and combining the communication information between the main card and the non-main card.
For example, a number card used by a user usually does not have a call or frequent calls, and if frequent calls exist between a main card and a non-main card, the main card and the non-main card can be indicated to be not used by the same person; on the contrary, if there is no call between the active card and the non-active card, and there is no other communication record on the non-active card, it can be determined that the two cards are used by the same person.
According to the embodiment, the number card under the existing identity card is classified according to the determined number card relation information and the service rule in combination with a call bank, whether the number card is used by the same person or not is accurately judged, and accurate marketing of one-line staff in the market to a plurality of number card users is realized, so that the resource investment is saved.
In an embodiment provided by the present application, the determining that the primary card is obtained according to the service information of the number card to be screened may include: judging the main package cost, ARPU (average of every 3 months), DOU (average of every 3 months) and MOU (average of every 3 months), wherein the highest number card is the main card; and judging that the number card transacted with the business needing to be transacted by the user is the main card.
Judging whether the main card and the non-main card can start from different dimensions:
the service information of the number card to be discriminated is used as a judgment dimension for judging the main card and the non-main card, and analysis and judgment can be rapidly carried out through the statistical data of the network operator. Wherein ARPU is Average income Per User (ARPU-Average received Per User), DOU is monthly Average traffic consumption Per client (Discharge Of Usage), and MOU is Average monthly call duration Per User (Minutes Of Usage). The highest card number in the main package cost, the ARPU (average number per month in nearly 3 months), the DOU (average number per month in nearly 3 months) and the MOU (average number per month in nearly 3 months) of a plurality of cards to be screened can be judged as the main card.
The method also comprises the steps of judging the number card transacted with the business needing to be transacted by the user as a main card; and obtaining the main card, setting the main card on the multi-card terminal, and judging the card to be identified as the own card if the IMEI number of the mobile phone terminal of the card to be identified is consistent with the IMEI number of the mobile phone terminal corresponding to the main card.
For the non-primary card judged and obtained according to the service information of the number card to be discriminated, the following dimensions can be included but not limited:
if the number card to be discriminated is in the multi-card terminal and the number card with the registration time earlier than that of the number card to be discriminated exists, the number card to be discriminated is judged to be a non-primary card;
and judging whether the calling card and the called card generate calling and called calls with the main card, wherein the number card with the average call duration larger than the preset call duration is a non-main card.
In the embodiment, the condition of the number card is simply and effectively preliminarily judged through the conditions of different dimensions.
Referring to fig. 3, fig. 2 is a schematic diagram illustrating a method for determining number card call similarity according to an embodiment of the present application; in an embodiment of the present application, determining to obtain a card number usage result according to communication information between a primary card and a non-primary card may include:
if the proportion of the non-answering behavior in the conversation behaviors of the main card and the non-main card is larger than a preset non-answering threshold, judging that the main card and the non-main card are used by the same person;
and if the ratio of the same number of the opposite terminals dialed by the user is greater than the preset opposite terminal dialing threshold value, judging that the main card A and the non-main card B are used by the same person.
And the method can also be used according to the call non-answering rate: and mining and distinguishing the user number card and the non-user number card based on the number of the user calls, wherein if the ratio of the call behaviors of the two number cards is higher, the probability that the card is used by the same person is higher. The calculation formula is as follows:
the number of times of the call behavior is represented, and the number of times of the call behavior comprises a call answering situation and a call non-answering situation.
Similarity of opposite call ends: the more the number of the opposite terminal dialed by the user is the same, the more the two number cards are similar in conversation, the higher the probability of being used by the same person is; the calculation formula is as follows:
the classification of the main card and the non-main card is obtained through the preliminary judgment result of the service information, and then the use condition of the number card is judged based on the communication data between the main card and the non-main card. The method is mainly used for judging whether the main card and the non-main card are used by the same person or not.
For example, if the same user transacts two number cards in sequence by using the same identity card and the number cards are used by the same person; for operators, if short message push marketing, telephone notification marketing and the like are performed on all number cards, manpower and material resources are undoubtedly increased, and resource waste is caused. When the service condition of the number card is judged, only the main card is pushed, so that resources are saved, and accurate marketing is realized.
Referring to fig. 2 to fig. 3, fig. 2 is a schematic diagram illustrating a method for calculating call similarity of a number card in a number card usage determination method according to an embodiment of the present application, and fig. 3 is a diagram illustrating a prefix tree generated based on a base station sequence table in a number card usage determination method according to an embodiment of the present application;
in one embodiment of the application, a number card use result is judged and obtained according to communication and interaction information between a main card and a non-main card; specifically, the method for judging the contact ratio of the active track base station between the main card and the non-main card comprises the following steps:
step N1: acquiring data of base stations where a main card and a non-main card are located;
for example: acquiring base station data of a user every day, dividing a time period into 6 blocks, and selecting a resident base station of the user in 6 time periods, as shown in table 1:
| time period | Resident base station |
| 0 point to 4 points | A |
| 4 point-8 point | B |
| 8 points to 12 points | C |
| 12 points to 16 points | D |
| 16 to 20 points | E |
| 20 points to 24 points | F |
Step N2: sequencing according to the occurrence frequency of the base station, and respectively generating a frequent item set base station sequence list;
the method comprises the following steps of utilizing a neural network algorithm to mine a frequent item set, sorting base station sequence tables of each day for base station conditions of n days according to base station sequence information and sorting according to occurrence times, and rejecting base stations with occurrence times less than n times to generate a frequent item set base station sequence table as shown in table 2:
| number of days | Base station screening |
| 1 | {F，D，E} |
| 2 | {F，D，E} |
| 3 | {F，D，E} |
| 4 | {F，D，E，B} |
| 5 | {F，D，B} |
| 6 | {F，A} |
| … | … |
| n | {F，M} |
Step N3: calculating a first contact ratio of a frequent item set of a base station where a main card and a non-main card are located;
in the step N3, a frequent item set can be mined by utilizing an FP-Growth algorithm for the calculation of the contact ratio; establishing a prefix tree T according to the generated base station sequence table, and obtaining a prefix tree T according to the previous 5 days (set as working days) of the table as shown in the figure 3;
step N4: traversing T in a depth-first mode, and finally obtaining a base station frequent item set P1 { { F, D }, { F, D, E } } of a number working day activity track, and calculating a working day activity track base station frequent item set P2 of a second number in the same way;
step N5: calculating the contact ratio of the frequent item sets P1 and P2 of the base station, wherein the calculation is as shown in formula (1):
step N6: calculating coincidence values of two mobile phone numbers including workday, saturday and sunday according to the steps N1-N5, and outputting to form three dimensional indexes: the contact ratio of the frequent item sets of the workday base stations, the contact ratio of the frequent item sets of the saturday base stations and the contact ratio of the frequent item sets of the sunday base stations.
If the coincidence degree of the moving track base stations of the two cards is higher, the probability of using the same person is higher; specifically, if the contact ratio is greater than the preset activity contact ratio threshold value, it is determined that the primary card and the non-primary card are used by the same person.
In an embodiment of the present application, the determination may be made according to the overlap ratio of the staying track base station between the active card and the non-active card:
respectively screening out resident base stations of the main card and the non-main card within a preset time period;
judging the second overlapping degree of the base station where the main card and the non-main card are positioned in the same time slot;
and if the second coincidence degree is larger than the preset dwell coincidence degree threshold value, judging that the main card and the non-main card are used by the same person.
For example: and calculating the base station with the longest residence time in three time periods of busy working days, idle working days and weekends for obtaining the two mobile phone numbers. Note: the working day is 7:00am-7:00pm in busy working days, and is 7:00pm-7:00am in idle working days;
whether the three time quantum resident base station numbers of working day busy hour, working day idle hour, weekend that match two cell-phone numbers respectively are unanimous, if unanimous then output 1, if inconsistent then output 0, output forms three dimension index: whether the resident base stations on busy days are consistent, whether the resident base stations on idle days are consistent and whether the resident base stations on weekends are consistent. If the stay type track base stations tend to be consistent, the probability of being used by the same person is higher. If the coincidence degree of the moving track base stations of the two cards is higher, the probability of using the same person is higher; specifically, if the contact ratio is greater than a preset active contact ratio threshold value, the primary card and the non-primary card are judged to be used by the same person.
The embodiment starts from two dimensions of a flowing track and a staying track, wherein the flowing track is based on a current-day action track chain of a user, base station frequent item sets of a user working day, a saturday and a sunday are mined through an FP-Growth algorithm, and the contact ratio of the base station frequent item sets of two numbers (a main card and a non-main card) is calculated through a contact ratio formula; the stay type base station is used for firstly excavating the resident base stations of the user in busy working days, idle working days and weekends, and then comparing whether the resident base stations of the two numbers are consistent or not to be used as a basis for judging whether the two numbers are used by the same person or not.
Referring to fig. 4, fig. 4 is a flowchart illustrating a method for determining card number usage according to an embodiment of the present application; in an embodiment of the application, the call similarity characteristic and the contact ratio of the base station of the movable track are integrated on the basis of the number card service information, so that the probability that the number cards are used by the same person is obtained. May include the steps of:
the method comprises the following steps: integrating the call similarity characteristic and the data calculated by the contact ratio of the base station of the moving track as a sample to be predicted
Wherein S1For cards to be discriminated under the same ID card, S3Number cards which are not the main card and the non-main card;
m2is the sample size, n1A field feature number;
step two: screening data set S1Non-primary card sample S in2Obtaining a model positive sample A1(ii) a Screening data set S2Obtaining a model negative sample B1；
Step three: based on the input positive sample A1And negative sample B1The data set respectively calculates the call similarity and the contact ratio of the mobile track base station with the main card number, and the data set is used as the sample characteristic of the model training test to output a modeling sample
Step four: inputting a modeling sample B, dividing the modeling sample AB according to the proportion of 7:3 to obtain a model training set A11、B11Model test set A12、B12；
Step five: inputting training data set A by using classification algorithm such as logistic regression, random forest or GBDT11And B11Model training is performed, testing data set A12、B12Adjusting the optimal parameters and outputting a natural person identification model;
step six: and C, predicting the data set to be predicted in the card identification model, outputting the probability vector of the card, and outputting the prediction result of the model.
In the embodiment, by means of the service characteristic data and in combination with the conditions of similarity of conversation behaviors between the number cards of the users and track coincidence degree, the number card screening models for personal use and non-personal use of the multi-card users are constructed, the problem of identifying whether the lower number card of the one-card user is used by the user is solved, and the function of screening the number card for natural use of the one-card user is realized.
In an embodiment of the present application, a method for verifying an upper prediction result is further provided, including the following steps:
inputting a data set C to be predicted and a personal card probability vector p1And outputting the prediction effect of the model.
The method comprises the following steps: adding a column of real category identification vector y in the data set C to be predicted, if the card is the master card S1If the number is the number of the same terminal, the real category identification vector y is 1, otherwise, y is 0, and the new data set is marked as D;
step two: obtaining a predictor vector p by the last module1Establishing a confusion matrix with the true class identification vector y of the data set D, the confusion matrix format being as follows (table 3):
step three: precision (Precision) and Recall (Recall) were calculated as follows (formula 2-formula 3):
step four: and verifying the prediction result of the use condition of the number card according to the precision ratio and the recall ratio.
The embodiment provides that the primary card and the non-primary card under the condition of one card with multiple numbers are pre-judged according to the service information of the number card, and then the accurate judgment of the use condition of the number card is realized based on the communication and interaction information. The method and the device have the advantages that the personal use and non-personal use number card discriminating models for the multi-card users are constructed by combining the conditions of similarity and track contact ratio of conversation behaviors between the user number cards, the problem of identifying whether the number card of the one-card multi-card user is used by the user under the one-card multi-card user is solved, the function of discriminating the number card of the one-card multi-card user by using the natural person is realized, the condition of using the same person by using the number card is accurately judged, and the accurate marketing of one-line personnel in the market to the multi-number card users is realized, so that the resource investment is saved.
Fig. 5 is a schematic structural diagram of a device for determining number card usage according to an embodiment of the present application. As shown in fig. 5, the apparatus may include a data acquisition module 210, a business rule determination module 220, a result determination module 230, a feature integration model processing module 240, and an effect verification module 250.
The data acquisition module 210 is configured to extract all number cards to be screened from the same identity card;
the service rule judging module 220 is used for judging to obtain a main card and a non-main card according to the service information of the number card to be discriminated;
the result determining module 230 is configured to determine to obtain a card number using result according to the communication information of the primary card and the non-primary card.
The result determination module 230 includes:
a call similarity feature unit 231, configured to determine whether the primary card and the non-primary card are used by the same person according to communication information of the primary card and the non-primary card;
the activity track base station overlap ratio calculation unit 232 is configured to determine whether the active card and the non-active card are used by the same person according to the overlap ratio of the information of the base stations where the active card and the non-active card are located.
The feature integration model processing module 240 is configured to calculate a main card probability vector indicating that the main card and the non-main card are the same person in use probability according to data output by the call similarity feature module and the activity track base station overlap ratio calculation module;
and the effect verification module 250 is used for obtaining the accuracy rate, the recall rate and the accuracy rate of the card number using result according to the card probability vector of the user.
Each module/unit in the apparatus shown in fig. 5 has a function of implementing each step in fig. 1 to fig. 4, and can achieve the corresponding technical effect, and for brevity, no further description is provided herein.
Fig. 6 is a schematic diagram illustrating a hardware structure of a number card use judgment device according to an embodiment of the present application.
The card-in-use determination device may include a processor 301 and a memory 302 storing computer program instructions.
Specifically, the processor 301 may include a Central Processing Unit (CPU), an Application Specific Integrated Circuit (ASIC), or one or more Integrated circuits configured to implement the embodiments of the present Application.
In one example, the Memory 302 may be a Read Only Memory (ROM). In one example, the ROM may be mask programmed ROM, programmable ROM (prom), erasable prom (eprom), electrically erasable prom (eeprom), electrically rewritable ROM (earom), or flash memory, or a combination of two or more of these.
The memory 302 may include Read Only Memory (ROM), Random Access Memory (RAM), magnetic disk storage media devices, optical storage media devices, flash memory devices, electrical, optical, or other physical/tangible memory storage devices. Thus, in general, the memory includes one or more tangible (non-transitory) computer-readable storage media (e.g., memory devices) encoded with software comprising computer-executable instructions and when the software is executed (e.g., by one or more processors), it is operable to perform operations described with reference to the methods according to an aspect of the present disclosure.
The processor 301 reads and executes the computer program instructions stored in the memory 302 to implement the methods/steps S1 to S4 in the embodiments shown in fig. 1 to 4, and achieve the corresponding technical effects achieved by the embodiments shown in fig. 1 to 4 executing the methods/steps thereof, which are not described herein again for brevity.
In addition, in combination with the number card use determination method in the above embodiment, the embodiment of the present application may provide a computer storage medium to implement. The computer storage medium having computer program instructions stored thereon; the computer program instructions, when executed by a processor, implement the method for determining card usage of any number in the above embodiments.
It is to be understood that the present application is not limited to the particular arrangements and instrumentality described above and shown in the attached drawings. A detailed description of known methods is omitted herein for the sake of brevity. In the above embodiments, several specific steps are described and shown as examples. However, the method processes of the present application are not limited to the specific steps described and illustrated, and those skilled in the art can make various changes, modifications, and additions or change the order between the steps after comprehending the spirit of the present application.
The functional blocks shown in the above-described structural block diagrams may be implemented as hardware, software, firmware, or a combination thereof. When implemented in hardware, it may be, for example, an electronic Circuit, an Application Specific Integrated Circuit (ASIC), suitable firmware, plug-in, function card, or the like. When implemented in software, the elements of the present application are the programs or code segments used to perform the required tasks. The program or code segments can be stored in a machine-readable medium or transmitted by a data signal carried in a carrier wave over a transmission medium or a communication link. A "machine-readable medium" may include any medium that can store or transfer information. Examples of a machine-readable medium include electronic circuits, semiconductor memory devices, ROM, flash memory, Erasable ROM (EROM), floppy disks, CD-ROMs, optical disks, hard disks, fiber optic media, Radio Frequency (RF) links, and so forth. The code segments may be downloaded via computer networks such as the internet, intranet, etc.
It should also be noted that the exemplary embodiments mentioned in this application describe some methods or systems based on a series of steps or devices. However, the present application is not limited to the order of the above-described steps, that is, the steps may be performed in the order mentioned in the embodiments, may be performed in an order different from the order in the embodiments, or may be performed simultaneously.
Aspects of the present disclosure are described above with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the disclosure. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, enable the implementation of the functions/acts specified in the flowchart and/or block diagram block or blocks. Such a processor may be, but is not limited to, a general purpose processor, a special purpose processor, an application specific processor, or a field programmable logic circuit. It will also be understood that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware for performing the specified functions or acts, or combinations of special purpose hardware and computer instructions.
As described above, only the specific embodiments of the present application are provided, and it can be clearly understood by those skilled in the art that, for convenience and brevity of description, the specific working processes of the system, the module and the unit described above may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again. It should be understood that the scope of the present application is not limited thereto, and any person skilled in the art can easily conceive various equivalent modifications or substitutions within the technical scope of the present application, and these modifications or substitutions should be covered within the scope of the present application.
Claims (14)
1. A method for judging number card use is characterized by comprising the following steps:
extracting all number cards to be discriminated under the same identity card;
judging to obtain a main card and a non-main card according to the service information of the number card to be discriminated;
and judging to obtain the card number using result according to the communication and interaction information of the main card and the non-main card.
2. The card number use judgment method according to claim 1, wherein judging to obtain a primary card according to the service information of the card number to be screened comprises:
judging the main package cost, ARPU (average every 3 months), DOU (average every 3 months) and MOU (average every 3 months), wherein the highest card is the main card;
and judging that the number card transacted with the business needing to be transacted by the user is the main card.
3. The card number use judgment method according to claim 1, wherein judging to obtain a non-primary card according to the service information of the card number to be screened comprises:
if the number card to be discriminated is in the multi-card terminal and a number card with registration time earlier than that of the number card to be discriminated exists, judging that the number card to be discriminated is a non-primary card;
and judging whether the calling card and the called card generate calling and called calls with the main card, wherein the number card with the average call duration larger than the preset call duration is a non-main card.
4. The method of claim 1, wherein determining whether to obtain a card usage result according to communication information between the primary card and the non-primary card comprises:
if the proportion of the non-answering behavior in the conversation behaviors of the main card and the non-main card is larger than a preset non-answering threshold, judging that the main card and the non-main card are used by the same person;
and if the same proportion of the numbers of the opposite terminals dialed by the user is greater than a preset opposite terminal dialing threshold value, judging that the main card and the non-main card are used by the same person.
5. The method of claim 1, wherein determining whether to obtain a card usage result according to communication information between the primary card and the non-primary card comprises:
acquiring data of base stations where the main card and the non-main card are located;
sequencing according to the occurrence frequency of the base station, and respectively generating a frequent item set base station sequence list;
calculating a first contact ratio of a frequent item set of the base station where the main card and the non-main card are located;
and if the first contact ratio is greater than a preset movable contact ratio threshold value, judging that the main card and the non-main card are used by the same person.
6. The card number use judgment method according to claim 5, further comprising:
respectively screening out resident base stations of the main cards and the non-main cards within a preset time period;
judging the second overlapping degree of the base station where the main card and the non-main card are positioned in the same time slot;
and if the second coincidence degree is larger than a preset staying coincidence degree threshold value, judging that the main card and the non-main card are used by the same person.
7. The method of claim 1, wherein determining whether to obtain a card usage result according to communication information of the primary card and the non-primary card comprises:
screening a data set to be detected consisting of the number cards to be screened;
obtaining a non-main card user sample in the main card, and obtaining a model positive sample; obtaining a non-main card user sample in the non-main card, and obtaining a model negative sample;
respectively calculating the call similarity and the activity track base station contact ratio of the model positive sample and the model negative sample with the main card;
establishing a number card recognition neural network model based on the call similarity and the contact ratio of the moving track base station;
processing the data set of the number card to be discriminated by using the number card recognition neural network model to obtain a self-use probability vector;
and judging to obtain the number card use result according to the self-use probability vector.
8. The card number use judgment method of claim 7, wherein the step of calculating the call similarity and the activity track base station contact ratio between the model positive sample and the master card and between the model negative sample and the master card respectively comprises:
and calculating the contact ratio of the movable track base station by utilizing an FP-Growth algorithm.
9. The card number use judgment method according to claim 7, further comprising:
adding category identification vectors in the data set to be detected to obtain a prediction data set; if the number card to be discriminated is the same terminal number card as the main card, the category identification vector is 1; if not, the category identification vector is 0;
establishing a confusion matrix according to the prediction data set and the self-use probability vector;
and obtaining the accuracy, the recall rate and the accuracy of the card number using result according to the confusion matrix.
10. A number card use judgment device, comprising:
the data acquisition module is used for extracting all the number cards to be discriminated under the same identity card;
the business rule judging module is used for judging to obtain a main card and a non-main card according to the business information of the number card to be discriminated;
and the result judging module is used for judging to obtain the number card using result according to the communication and interaction information of the main card and the non-main card.
11. The card number use judgment device according to claim 10, wherein the result judgment module comprises:
the call similarity characteristic module is used for judging whether the main card and the non-main card are used by the same person or not according to the communication and interaction information of the main card and the non-main card;
and the movable track base station contact ratio calculation module is used for judging whether the main card and the non-main card are used by the same person or not according to the contact ratio of the information of the base stations where the main card and the non-main card are located.
12. The card use judgment device according to claim 11, further comprising:
the feature integration model processing module is used for calculating a main card probability vector of the use probability of the main card and the non-main card for the same person according to data output by the call similarity feature module and the activity track base station contact ratio calculating module;
and the effect verification module is used for obtaining the accuracy rate, the recall rate and the accuracy rate of the card number using result according to the personal card probability vector.
13. A number card use judgment device, characterized by comprising: a processor, and a memory storing computer program instructions; the processor reads and executes the computer program instructions to realize the number card use judgment method according to any one of claims 1 to 9.
14. A computer storage medium having stored thereon computer program instructions which, when executed by a processor, implement the card number usage determination method of any one of claims 1 to 9.
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