CN110351442B - Seat message prompting method and device, computer equipment and storage medium - Google Patents
Seat message prompting method and device, computer equipment and storage medium Download PDFInfo
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- CN110351442B CN110351442B CN201910493449.9A CN201910493449A CN110351442B CN 110351442 B CN110351442 B CN 110351442B CN 201910493449 A CN201910493449 A CN 201910493449A CN 110351442 B CN110351442 B CN 110351442B
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- H04—ELECTRIC COMMUNICATION TECHNIQUE
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- H04M3/00—Automatic or semi-automatic exchanges
- H04M3/42—Systems providing special services or facilities to subscribers
- H04M3/50—Centralised arrangements for answering calls; Centralised arrangements for recording messages for absent or busy subscribers ; Centralised arrangements for recording messages
- H04M3/51—Centralised call answering arrangements requiring operator intervention, e.g. call or contact centers for telemarketing
- H04M3/5166—Centralised call answering arrangements requiring operator intervention, e.g. call or contact centers for telemarketing in combination with interactive voice response systems or voice portals, e.g. as front-ends
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Abstract
The invention discloses a seat message prompting method, a seat message prompting device, computer equipment and a storage medium. The method comprises the following steps: if detecting that a contact list distributed by a server is received, acquiring the contact list through a trigger, and displaying the contact list; dialing the contact numbers corresponding to the contact persons according to the contact person sequence of the contact list; if a connection instruction of a contact person is detected, establishing connection with the contact person corresponding to the connection instruction, and if the call is ended, acquiring and storing voice information; and if the contact data with the seat contact state identifier field value of 0 exists in the contact list at a preset detection time point, writing the corresponding contact data into a recovery data table. The method adopts a system performance optimization technology, realizes that the contact list is obtained by the timer and is sent to the seat end for automatic dialing communication, avoids repeated scanning and sending of high frequency, and reduces the consumption of system resources.
Description
Technical Field
The invention relates to the technical field of system performance optimization, in particular to a seat message prompting method and device, computer equipment and a storage medium.
Background
At present, in a retail seat marketing system, message reminding of a dispatch list is performed by scanning a message table once every 2 minutes by Quartz (Quartz is an open source job scheduling framework completely written by java), scanning out unread messages and pushing the unread messages to the front end to be presented to a seat, so that a repeated dispatch list which is not clicked and read by the seat exists in the dispatch list, and high-frequency repeated scanning and sending result in high consumption rate of system resources.
Disclosure of Invention
The embodiment of the invention provides an agent message prompting method, an agent message prompting device, computer equipment and a storage medium, and aims to solve the problem that in the prior art, an agent system regularly scans unread messages at high frequency and continuously pushes the unread messages to the agent front end, so that the consumption of system resources is high.
In a first aspect, an embodiment of the present invention provides an agent message prompting method, which includes:
if detecting that a contact list distributed by a server is received, acquiring the contact list through a trigger, and displaying the contact list;
dialing the contact numbers corresponding to the contact persons according to the contact person sequence of the contact list;
if a connection instruction of the contact person is detected, establishing connection with the contact person corresponding to the connection instruction, and if the call is finished, acquiring and storing voice information; and
and if the contact person data with the seat contact state identifier field value of 0 exists in the contact list at the preset detection time point, writing the corresponding contact person data into a recovery data table.
In a second aspect, an embodiment of the present invention provides an agent message prompting apparatus, including:
the trigger triggering unit is used for acquiring the contact list through a trigger and displaying the contact list if detecting that the contact list distributed by the server is received;
the automatic dialing unit is used for dialing the contact numbers corresponding to the contacts according to the contact sequence of the contact list;
the voice information acquisition unit is used for establishing connection with the contact corresponding to the connection instruction if the connection instruction of the contact is detected, and acquiring and storing voice information if the call is ended; and
and the data recovery unit is used for writing the corresponding contact data into a recovery data table if the contact data with the seat contact state identifier field value of 0 is detected to exist in the contact list at a preset detection time point.
In a third aspect, an embodiment of the present invention further provides a computer device, which includes a memory, a processor, and a computer program that is stored in the memory and is executable on the processor, where the processor implements the agent message prompting method according to the first aspect when executing the computer program.
In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium, where the computer-readable storage medium stores a computer program, and the computer program, when executed by a processor, causes the processor to execute the agent message prompting method according to the first aspect.
The embodiment of the invention provides a method and a device for prompting an agent message, computer equipment and a storage medium. The method comprises the steps that if a contact list distributed by a server is detected and received, the contact list is obtained through a trigger, and the contact list is displayed; dialing the contact numbers corresponding to the contact persons according to the contact person sequence of the contact list; if a connection instruction of a contact person is detected, establishing connection with the contact person corresponding to the connection instruction, and if the call is ended, acquiring and storing voice information; and if the contact data with the seat contact state identifier field value of 0 exists in the contact list at a preset detection time point, writing the corresponding contact data into a recovery data table. The method adopts a system performance optimization technology, realizes that the contact list is obtained by the timer and is sent to the seat end for automatic dialing communication, avoids repeated scanning and sending of high frequency, and reduces the consumption of system resources.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
Fig. 1 is a schematic flow chart of an agent message prompting method according to an embodiment of the present invention;
fig. 2 is another schematic flow chart of a method for prompting an agent message according to an embodiment of the present invention;
fig. 3 is another schematic flow diagram of an agent message prompting method according to an embodiment of the present invention;
fig. 4 is a schematic sub-flow diagram of an agent message prompting method according to an embodiment of the present invention;
fig. 5 is another schematic flow chart of a seat message prompting method according to an embodiment of the present invention;
fig. 6 is a schematic block diagram of an agent message prompting apparatus according to an embodiment of the present invention;
fig. 7 is another schematic block diagram of an agent message prompting apparatus according to an embodiment of the present invention;
fig. 8 is another schematic block diagram of an agent message prompting device according to an embodiment of the present invention;
fig. 9 is a schematic block diagram of a sub-unit of an agent message prompting device according to an embodiment of the present invention;
fig. 10 is another schematic block diagram of an agent message prompting device according to an embodiment of the present invention;
FIG. 11 is a schematic block diagram of a computer device provided by an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It will be understood that the terms "comprises" and/or "comprising," when used in this specification and the appended claims, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
It is also to be understood that the terminology used in the description of the invention herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used in this specification and the appended claims, the singular forms "a", "an", and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.
It should be further understood that the term "and/or" as used in this specification and the appended claims refers to and includes any and all possible combinations of one or more of the associated listed items.
Referring to fig. 1, fig. 1 is a schematic flow chart of an agent message prompting method according to an embodiment of the present invention, where the agent message prompting method is applied to a server and is executed by application software installed in the server.
As shown in fig. 1, the method includes steps S110 to S140.
S110, if detecting that a contact list distributed by a server is received, acquiring the contact list through a trigger, and displaying the contact list; the contact list comprises at least one piece of contact data, and each piece of contact data comprises a contact name field, a contact number field and an agent contact state identifier field.
In this embodiment, if the retail seat marketing system (which may be understood as a server) only issues a contact list to the seat end at regular time every day, when the seat end receives the contact list, the trigger is started to acquire the contact list, and the contact list is sent to the display of the seat end for display. Each piece of data in the contact list at least comprises a contact name field, a contact number field and an agent contact state identifier field; the seat contact state identifier field is used for indicating whether the seat end contacts the other party after checking the user information in the data and successfully establishes the contact (namely, successfully establishes the contact, namely, connects to the telephone).
In one embodiment, step S110 includes:
and acquiring the contact list by starting a DML trigger.
In the present embodiment, a DML trigger (the full name of DML is Data management Language, which represents one of the classifications of SQL) is similar to a function and a procedure, which are program entity units having a declaration section, an execution section, and an exception handling section.
The trigger must be stored in the database as the identity of the individual object. The trigger runs implicitly when an event occurs, cannot receive parameters, and cannot be invoked. The way a trigger is run is called a firing trigger, and the triggering event can be a DML (INSERT, UPDATE, or DELETE) operation on a database table or an operation of some view.
The trigger event includes INSERT, UPDATE or DELETE, and the trigger timing has two BEFORE and AFTER, and can occur BEFORE the trigger event or AFTER the trigger event.
Namely, once the agent end detects the contact list distributed by the server, the DML trigger is immediately started to perform subsequent data operation, so that the problem that the contact list is scanned every 2 minutes by adopting a quartz timer in the prior art, and unread data in the contact list is repeatedly sent to a display of the agent end to be displayed is avoided.
And S120, dialing the contact numbers corresponding to the contacts according to the contact sequence of the contact list.
In this embodiment, after the agent end receives the contact list, the agent end can automatically dial the numbers of the contacts according to the sequence of the contacts in the contact list, and by means of automatic dialing, the efficiency is improved, and the agent end does not need to dial manually to establish contact with a client.
S130, if a connection instruction of the contact person is detected, connection is established with the contact person corresponding to the connection instruction, and if the call is finished, voice information is obtained and stored.
In this embodiment, after the seat end receives the contact list, the seat end may automatically dial the contact numbers in sequence according to the order of the contacts in the contact list, and then transfer to the seat for manual communication after the contact corresponding to the contact number makes a call, and record the voice information corresponding to the record during the communication process, and store the voice information after the call is finished, so as to be used for subsequent quality inspection.
In an embodiment, as shown in fig. 2, step S130 is followed by:
s131, setting the value of an agent contact state identifier field in the data of the corresponding contact in the contact list to be 1.
In this embodiment, when the agent end receives the contact list and establishes a contact with each contact in the contact list successfully through dialing, it indicates that the agent end has successfully contacted with the contact, and at this time, in order to distinguish from the unsuccessfully contacted contact, the value of the agent contact state identifier field in the corresponding data in the contact list of the contact corresponding to the connection instruction may be set to 1. If the contact is not successfully established after the agent terminal dials one or more contact persons in the contact list, setting the value of the corresponding agent contact state identifier field of the contact person in the contact list to be 0 so as to represent that the contact is successfully established with the contact person. Through the seat contact state identifier field, whether the seat end is successfully connected with the contact person or not is effectively distinguished.
In an embodiment, as shown in fig. 3, after step S130, the method further includes:
s132, receiving voice information, and recognizing the voice information through a pre-trained N-gram model to obtain a recognition result;
and S133, extracting keywords from the recognition result to obtain a keyword set corresponding to the recognition result.
In this embodiment, the N-gram Model is a Language Model (LM), which is a probabilistic-based discriminant Model whose input is a sentence (sequential sequence of words) and output is the probability of the sentence, i.e., the joint probability of the words. And when the speech to be recognized is recognized through the N-gram model and a whole sentence is obtained through recognition, the speech to be recognized can be effectively recognized through the N-gram model, and the sentence with the maximum recognition probability is obtained as a recognition result.
In one embodiment, as shown in fig. 4, step S133 includes:
s1331, segmenting the recognition result through a probability statistics-based segmentation model to obtain a corresponding segmentation result;
and S1332, extracting the keyword information before the preset ranking value in the word segmentation result through a word frequency-inverse text frequency index model to be used as a keyword set corresponding to the recognition result.
In this embodiment, the process of segmenting the recognition result by the word segmentation model based on probability statistics is as follows:
for example, let C = C1C2.. Cm, C be the chinese string to be cut, let W = W1W2.. Wn, W be the result of the cut, wa, wb, \8230;, wk be all possible cut schemes for C. Then, based on the probability statistics word segmentation model, the target word string W can be found, so that W satisfies: p (W | C) = MAX (P (Wa | C), P (Wb | C).. P (Wk | C)), and the word string W obtained by the word segmentation model is a word string with the maximum estimated probability. Namely:
for a substring S to be participled, all candidate words w1, w2, \8230, wi, \8230, wn are taken out in the order from left to right; finding out the probability value P (wi) of each candidate word in a dictionary, and recording all left neighbors of each candidate word; calculating the cumulative probability of each candidate word, and simultaneously comparing to obtain the best left neighbor word of each candidate word; if the current word wn is the tail word of the string S and the accumulated probability P (wn) is the maximum, wn is the end word of S; and (4) sequentially outputting the optimal left neighbor of each word from wn to S in the order from right to left, namely, the word segmentation result of S.
And after the word segmentation result corresponding to the recognition result is obtained, extracting keyword information before a preset ranking value in the word segmentation result as a keyword set through a word Frequency-Inverse text Frequency index model (namely a TF-IDF model, wherein the TF-IDF is short for Term Frequency-Inverse Document Frequency). Extracting keyword information before a preset ranking value in the word segmentation result through a TF-IDF model, wherein the keyword information is as follows:
1) Calculating the word frequency of each word i in the word segmentation result, and recording as TF i;
2) Calculating the inverse document frequency IDF i of each word segmentation i in the word segmentation result;
when calculating the inverse document frequency IDF i of each word segmentation i, a corpus (similar to a dictionary in the word segmentation process) is needed to simulate the use environment of the language;
the inverse document frequency IDF i = lg [ total number of documents in the corpus/(number of documents containing the participle + 1) ];
if a word is more common, then the greater the denominator, the closer to 0 the inverse document frequency. The denominator is increased by 1 in order to avoid a denominator of 0 (i.e., all documents do not contain the word).
3) Calculating a word frequency-inverse text frequency index TF-IDF i corresponding to each participle i in the participle result according to the TF i and the IDF i;
it is clear that TF-IDF is proportional to the number of occurrences of a word in a document and inversely proportional to the number of occurrences of the word in the entire language. Therefore, the keywords are automatically extracted, namely the TF-IDF value of each participle of the document is calculated, and then the words with the top N bits are taken as the keyword list of the document in descending order.
4) And sorting the word frequency-inverse text frequency indexes corresponding to each word in the word segmentation result in a descending order, and taking the words with the ranking before a preset ranking value (for example, the preset ranking value is 6) to form a keyword set corresponding to the recognition result.
The voice information is subjected to voice recognition and keyword extraction to obtain the keyword set corresponding to the voice information, so that the quality inspection post can conveniently carry out spot check quality inspection on the voice information corresponding to the keyword search, the problem that the voice information cannot be directly retrieved through quality inspection is avoided, and the search efficiency is improved.
In an embodiment, as shown in fig. 5, step S133 is followed by:
s134, obtaining the keywords with the word frequency-inverse text frequency index as the maximum value in the keyword set, using the keywords as target keywords, positioning the time points of the target keywords in the recognition result, and marking the keywords.
In this embodiment, in order to mark a keyword for each segment of speech to be recognized, a keyword with a maximum word frequency-inverse text frequency index in the keyword set may be first obtained as a target keyword, and then the target keyword is marked at a time point in the speech to be recognized (similar to marking a climax part of a song). Therefore, quality testing personnel can clearly know which key parts to listen to, time is saved, the head and the tail do not need to be heard, and quality testing efficiency is improved.
And S140, if the contact data with the seat contact state identifier field value of 0 exists in the contact list at the preset detection time point, writing the corresponding contact data into a recovery data table.
In this embodiment, if the retail seat marketing system issues the contact list to the seat end, after the seat end contacts the contact persons according to the contact list in sequence, data with a seat contact state identifier field value of 0 exists in the contact list, and the data may be that the seat end does not need to contact again after completing the task today, and at this time, the un-contacted contact persons can be recycled to the server, so that the server randomly allocates the seat end again, and the data recycling utilization rate is improved.
The method realizes that the contact list is acquired by the timer and is sent to the seat end for automatic dialing communication, avoids repeated scanning and sending of high frequency, and reduces the consumption of system resources.
The embodiment of the invention also provides an agent message prompting device, which is used for executing any embodiment of the agent message prompting method. Specifically, referring to fig. 6, fig. 6 is a schematic block diagram of an agent message prompting device according to an embodiment of the present invention. The agent message presentation apparatus 100 may be disposed in a server.
As shown in fig. 6, the agent message presentation apparatus 100 includes a trigger triggering unit 110, an automatic dialing unit 120, a voice information acquisition unit 130, and a data recovery unit 140.
A trigger triggering unit 110, configured to, if detecting that a contact list distributed by a server is received, obtain the contact list through a trigger, and display the contact list; the contact list comprises at least one piece of contact data, and each piece of contact data comprises a contact name field, a contact number field and an agent contact state identifier field.
In this embodiment, if the retail seat marketing system (which may be understood as a server) only issues a contact list to the seat end at regular time every day, when the seat end receives the contact list, the trigger is started to acquire the contact list, and the contact list is sent to the display of the seat end for display. Each piece of data in the contact list at least comprises a contact name field, a contact number field and an agent contact state identifier field; the agent contact state identifier field is used for indicating whether the agent end contacts the other party and successfully establishes contact (i.e. successfully establishes contact, namely, connects to the telephone) after checking the user information in the data.
In an embodiment, the trigger triggering unit 110 is specifically configured to:
and acquiring the contact list by starting a DML trigger.
In the present embodiment, a DML trigger (the full name of DML is Data management Language, which represents one of the classifications of SQL) is similar to a function and a procedure, which are program entity units having a declaration section, an execution section, and an exception handling section.
The triggers must be stored in the database as the identity of the individual objects. The trigger runs implicitly when an event occurs, cannot receive parameters, and cannot be invoked. The way a trigger is run is called a firing trigger, and the triggering event can be a DML (INSERT, UPDATE, or DELETE) operation on a database table or an operation of some view.
The trigger event includes INSERT, UPDATE or DELETE, and the trigger timing has two BEFORE and AFTER, and can occur BEFORE the trigger event or AFTER the trigger event.
Namely, once the agent end detects the contact list distributed by the server, the DML trigger is immediately started to perform subsequent data operation, so that the problem that the contact list is scanned every 2 minutes by adopting a quartz timer in the prior art, and unread data in the contact list is repeatedly sent to a display of the agent end to be displayed is avoided.
And the automatic dialing unit 120 is configured to dial the contact numbers corresponding to the contacts according to the contact sequence of the contact list.
In this embodiment, after the agent end receives the contact list, the agent end can automatically dial the numbers of the contacts according to the sequence of the contacts in the contact list, and by means of automatic dialing, the efficiency is improved, and the agent end does not need to dial manually to establish contact with a client.
The voice information obtaining unit 130 is configured to, if a connection instruction of a contact is detected, establish connection with the contact corresponding to the connection instruction, and obtain and store voice information if a call is completed.
In this embodiment, after the seat end receives the contact list, the seat end may automatically dial the contact numbers in sequence according to the sequence of the contacts in the contact list, and then transfer to the seat for manual communication after the contacts corresponding to the contact numbers are called, record the voice in the communication process, and store the voice information corresponding to the record after the call is finished, so as to be used as a subsequent quality inspection.
In one embodiment, as shown in fig. 7, the agent message prompting apparatus 100 further includes:
a field value setting unit 131, configured to set a value of an agent contact state identifier field in the data of the corresponding contact in the contact list to 1.
In this embodiment, when the agent end receives the contact list and establishes a contact with each contact in the contact list successfully through dialing, it indicates that the agent end has successfully contacted with the contact, and at this time, in order to distinguish from the unsuccessfully contacted contact, the value of the agent contact state identifier field in the corresponding data in the contact list of the contact corresponding to the connection instruction may be set to 1. If the contact is not successfully established after the agent terminal dials one or more contact persons in the contact list, setting the value of the corresponding agent contact state identifier field of the contact person in the contact list to be 0 so as to represent that the contact is successfully established with the contact person. Through the identifier field of the agent contact state, whether the agent end is successfully contacted with the contact person or not is effectively distinguished.
In one embodiment, as shown in fig. 8, the agent message prompting apparatus 100 further includes:
the speech recognition unit 132 is configured to receive speech information, and recognize the speech information through a pre-trained N-gram model to obtain a recognition result;
a keyword extracting unit 133, configured to perform keyword extraction on the recognition result to obtain a keyword set corresponding to the recognition result.
In this embodiment, the N-gram Model is a Language Model (LM) which is a probability-based discriminant Model whose input is a sentence (the sequential sequence of words) and whose output is the probability of the sentence, i.e., the joint probability of the words. And when the speech to be recognized is recognized through the N-gram model and a whole sentence is obtained through recognition, the speech to be recognized can be effectively recognized through the N-gram model, and the sentence with the maximum recognition probability is obtained as a recognition result.
In one embodiment, as shown in fig. 9, the keyword extraction unit 133 includes:
a word segmentation unit 1331, configured to perform word segmentation on the recognition result through a probability-based statistical word segmentation model to obtain a corresponding word segmentation result;
a keyword set obtaining unit 1332, configured to extract, through a word frequency-inverse text frequency index model, keyword information before a preset ranking value in the word segmentation result, so as to serve as a keyword set corresponding to the recognition result.
In this embodiment, the word segmentation process of the recognition result by the word segmentation model based on probability statistics is as follows:
for example, let C = C1C2.. Cm, C is the chinese string to be cut, let W = W1W2.. Wn, W is the result of the segmentation, wa, wb, \8230 \ 8230;, wk is all possible segmentation schemes for C. Then, based on the probabilistic word segmentation model, the target word string W can be found, so that W satisfies: a segmentation model of P (W | C) = MAX (P (Wa | C), P (Wb | C).. P (Wk | C)), and a word string W obtained by the segmentation model is a word string with the maximum estimated probability. Namely:
for a substring S to be segmented, all candidate words w1, w2, \ 8230, wi, \8230, wn are taken out in the order from left to right; finding out the probability value P (wi) of each candidate word in a dictionary, and recording all left neighbors of each candidate word; calculating the cumulative probability of each candidate word, and simultaneously comparing to obtain the best left neighbor word of each candidate word; if the current word wn is the end word of the string S and the cumulative probability P (wn) is the maximum, wn is the end word of S; and (5) sequentially outputting the optimal left neighbor of each word from wn according to the sequence from right to left, namely the word segmentation result of S.
And after the word segmentation result corresponding to the recognition result is obtained, extracting keyword information before a preset ranking value in the word segmentation result as a keyword set through a word Frequency-Inverse text Frequency index model (namely a TF-IDF model, wherein the TF-IDF is short for Term Frequency-Inverse Document Frequency).
The voice information is subjected to voice recognition and keyword extraction to obtain the keyword set corresponding to the voice information, so that the quality inspection post can conveniently perform selective inspection quality inspection on the voice information corresponding to the keyword search, the problem that the voice information cannot be directly retrieved by the quality inspection is avoided, and the search efficiency is improved.
In one embodiment, as shown in fig. 10, the agent message prompting apparatus 100 further includes:
and a keyword identification unit 134, configured to obtain a keyword with a maximum word frequency-inverse text frequency index in the keyword set, to serve as a target keyword, locate a time point of the target keyword in the recognition result, and perform keyword tagging.
In this embodiment, in order to mark a keyword for each segment of speech to be recognized, a keyword with a maximum word frequency-inverse text frequency index in the keyword set may be first obtained as a target keyword, and then the target keyword is marked at a time point in the speech to be recognized (similar to marking a climax part of a song). Therefore, quality testing personnel can clearly know which key parts to listen to, time is saved, the head and the tail do not need to be heard, and quality testing efficiency is improved.
The data recovery unit 140 is configured to, if it is detected at a preset detection time point that there is contact data whose seat contact state identifier field value is 0 in the contact list, write the corresponding contact data into a recovery data table.
In this embodiment, if the retail seat marketing system issues the contact list to the seat end, after the seat end contacts the contact persons according to the contact list in sequence, data with a seat contact state identifier field value of 0 exists in the contact list, and the data may be that the seat end does not need to contact again after completing the task today, and at this time, the un-contacted contact persons can be recycled to the server, so that the server randomly allocates the seat end again, and the data recycling utilization rate is improved.
The device realizes that the timer acquires the contact list and sends the contact list to the seat end for automatic dialing communication, avoids repeated scanning and sending of high frequency, and reduces the consumption of system resources.
The agent message prompting apparatus may be implemented in the form of a computer program, which may be run on a computer device as shown in fig. 11.
Referring to fig. 11, fig. 11 is a schematic block diagram of a computer device according to an embodiment of the present invention. The computer device 500 is a server, and the server may be an independent server or a server cluster composed of a plurality of servers.
Referring to fig. 11, the computer device 500 includes a processor 502, memory, and a network interface 505 connected by a system bus 501, where the memory may include a non-volatile storage medium 503 and an internal memory 504.
The non-volatile storage medium 503 may store an operating system 5031 and a computer program 5032. The computer program 5032, when executed, may cause the processor 502 to perform an agent message alert method.
The processor 502 is used to provide computing and control capabilities that support the operation of the overall computer device 500.
The internal memory 504 provides an environment for the execution of the computer program 5032 in the non-volatile storage medium 503, and when the computer program 5032 is executed by the processor 502, the processor 502 may be caused to execute the agent message notification method.
The network interface 505 is used for network communication, such as providing transmission of data information. Those skilled in the art will appreciate that the configuration shown in fig. 11 is a block diagram of only a portion of the configuration associated with aspects of the present invention and is not intended to limit the computing device 500 to which aspects of the present invention may be applied, and that a particular computing device 500 may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.
Wherein the processor 502 is configured to execute the computer program 5032 stored in the memory to perform the following functions: if detecting that a contact list distributed by a server is received, acquiring the contact list through a trigger, and displaying the contact list; the contact list comprises at least one piece of contact data, and each piece of contact data comprises a contact name field, a contact number field and an agent contact state identifier field; dialing the contact numbers corresponding to the contact persons according to the contact person sequence of the contact list; if a connection instruction of a contact person is detected, establishing connection with the contact person corresponding to the connection instruction, and if the call is ended, acquiring and storing voice information; and if the contact person data with the seat contact state identifier field value of 0 exists in the contact list at the preset detection time point, writing the corresponding contact person data into a recovery data table.
In an embodiment, the processor 502, when executing the step of obtaining the contact list through the trigger, performs the following operations: and acquiring the contact list by starting a DML trigger.
In an embodiment, after executing the step of detecting a connection instruction of the contact, establishing a connection with the contact corresponding to the connection instruction, and acquiring and storing the voice information after the call is ended, the processor 502 further executes the following operations: setting the value of an agent contact state identifier field in the data of the corresponding contact in the contact list to be 1.
In an embodiment, after the step of executing the step of establishing a connection with the contact corresponding to the connection instruction if the connection instruction of the contact is detected, and acquiring and storing the voice information after the call is ended, the processor 502 further executes the following operations: receiving voice information, and recognizing the voice information through a pre-trained N-gram model to obtain a recognition result; and extracting keywords from the identification result to obtain a keyword set corresponding to the identification result.
In an embodiment, when the step of extracting the keywords from the recognition result to obtain the keyword set corresponding to the recognition result is executed, the processor 502 executes the following operations: performing word segmentation on the recognition result through a word segmentation model based on probability statistics to obtain a corresponding word segmentation result; and extracting the keyword information before a preset ranking value in the word segmentation result through a word frequency-inverse text frequency index model to be used as a keyword set corresponding to the recognition result.
In an embodiment, after executing the step of extracting the keyword from the recognition result by the root to obtain the keyword set corresponding to the recognition result, the processor 502 further executes the following operations: and acquiring the keywords with the word frequency-inverse text frequency index as the maximum value in the keyword set to serve as target keywords, positioning the time points of the target keywords in the identification result, and marking the keywords.
Those skilled in the art will appreciate that the embodiment of a computer device illustrated in fig. 11 does not constitute a limitation on the particular configuration of the computer device, and in other embodiments, the computer device may include more or fewer components than those illustrated, or some components may be combined, or a different arrangement of components. For example, in some embodiments, the computer device may only include a memory and a processor, and in such embodiments, the structures and functions of the memory and the processor are consistent with those of the embodiment shown in fig. 11, and are not described herein again.
It should be understood that, in the embodiment of the present invention, the Processor 502 may be a Central Processing Unit (CPU), and the Processor 502 may also be other general purpose processors, digital Signal Processors (DSPs), application Specific Integrated Circuits (ASICs), field Programmable Gate Arrays (FPGAs) or other Programmable logic devices, discrete Gate or transistor logic devices, discrete hardware components, and the like. Wherein a general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
In another embodiment of the invention, a computer-readable storage medium is provided. The computer readable storage medium may be a non-volatile computer readable storage medium. The computer-readable storage medium stores a computer program, wherein the computer program when executed by a processor implements the steps of: if detecting that a contact list distributed by a server is received, acquiring the contact list through a trigger, and displaying the contact list; dialing contact numbers corresponding to the contact persons according to the contact person sequence of the contact list; the contact list comprises at least one piece of contact data, and each piece of contact data comprises a contact name field, a contact number field and an agent contact state identifier field; if a connection instruction of a contact person is detected, establishing connection with the contact person corresponding to the connection instruction, and if the call is ended, acquiring and storing voice information; and if the contact person data with the seat contact state identifier field value of 0 exists in the contact list at the preset detection time point, writing the corresponding contact person data into a recovery data table.
In an embodiment, the obtaining the contact list through a trigger includes: and acquiring the contact list by starting a DML trigger.
In an embodiment, if the connection instruction of the contact is detected, establishing a connection with the contact corresponding to the connection instruction, and after acquiring and storing the voice information after the call is ended, further including: setting the value of an agent contact state identifier field in the data of the corresponding contact in the contact list to be 1.
In an embodiment, if a connection instruction of a contact is detected, establishing a connection with the contact corresponding to the connection instruction, and after acquiring and storing voice information after the call is ended, further including: receiving voice information, and recognizing the voice information through a pre-trained N-gram model to obtain a recognition result; and extracting keywords from the recognition result to obtain a keyword set corresponding to the recognition result.
In an embodiment, the extracting the keywords from the recognition result to obtain a keyword set corresponding to the recognition result includes: performing word segmentation on the recognition result through a word segmentation model based on probability statistics to obtain a corresponding word segmentation result; extracting the keyword information before a preset ranking value in the word segmentation result through a word frequency-inverse text frequency index model to be used as a keyword set corresponding to the recognition result.
In an embodiment, after the root performs keyword extraction on the recognition result to obtain a keyword set corresponding to the recognition result, the method further includes: and acquiring the keywords with the word frequency-inverse text frequency index as the maximum value in the keyword set to serve as target keywords, positioning the time points of the target keywords in the identification result, and marking the keywords.
It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described apparatuses, devices and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again. Those of ordinary skill in the art will appreciate that the elements and algorithm steps of the examples described in connection with the embodiments disclosed herein may be embodied in electronic hardware, computer software, or combinations of both, and that the components and steps of the examples have been described in a functional general in the foregoing description for the purpose of illustrating clearly the interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the technical solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
In the several embodiments provided in the present invention, it should be understood that the disclosed apparatus, device and method may be implemented in other manners. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the units is only a logical division, and there may be other divisions in actual implementation, or units with the same function may be grouped into one unit, for example, multiple units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may also be an electric, mechanical or other form of connection.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiments of the present invention.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a storage medium. Based on such understanding, the technical solution of the present invention essentially or partly contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a magnetic disk, or an optical disk, and various media capable of storing program codes.
While the invention has been described with reference to specific embodiments, it will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the spirit and scope of the invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (8)
1. A method for prompting an agent message is characterized by comprising the following steps:
if detecting that a contact list distributed by a server is received, acquiring the contact list through a trigger, and displaying the contact list; the contact list comprises at least one piece of contact data, and each piece of contact data comprises a contact name field, a contact number field and an agent contact state identifier field;
dialing contact numbers corresponding to the contact persons according to the contact person sequence of the contact list;
if a connection instruction of the contact person is detected, establishing connection with the contact person corresponding to the connection instruction, and if the call is finished, acquiring and storing voice information; and
if the contact data with the seat contact state identifier field value of 0 exists in the contact list at a preset detection time point, writing the corresponding contact data into a recovery data table;
if a connection instruction of the contact person is detected, establishing connection with the contact person corresponding to the connection instruction, and after the voice information is acquired and stored after the call is finished, further comprising:
setting the value of an agent contact state identifier field in the data of the corresponding contact in the contact list to be 1.
2. The agent message prompting method of claim 1, wherein the obtaining of the contact list through a trigger comprises:
and acquiring the contact list by starting a DML trigger.
3. The agent message prompting method according to claim 1, wherein if a connection instruction of a contact is detected, establishing connection with the contact corresponding to the connection instruction, and after acquiring and storing voice information after the call is finished, further comprising:
receiving voice information, and identifying the voice information through a pre-trained N-gram model to obtain an identification result;
and extracting keywords from the recognition result to obtain a keyword set corresponding to the recognition result.
4. The agent message prompting method according to claim 3, wherein the extracting the keywords from the recognition result to obtain a keyword set corresponding to the recognition result comprises:
performing word segmentation on the recognition result through a word segmentation model based on probability statistics to obtain a corresponding word segmentation result;
and extracting the keyword information before a preset ranking value in the word segmentation result through a word frequency-inverse text frequency index model to be used as a keyword set corresponding to the recognition result.
5. The agent message prompting method according to claim 4, wherein after extracting the keywords from the recognition result to obtain a keyword set corresponding to the recognition result, the method further comprises:
and acquiring the keywords with the word frequency-inverse text frequency index as the maximum value in the keyword set to serve as target keywords, positioning the time points of the target keywords in the identification result, and marking the keywords.
6. An agent message prompting device, comprising:
the trigger triggering unit is used for acquiring the contact list through a trigger and displaying the contact list if detecting that the contact list distributed by the server is received;
the automatic dialing unit is used for dialing the contact numbers corresponding to the contacts according to the sequence of the contacts in the contact list; the contact list comprises at least one piece of contact data, and each piece of contact data comprises a contact name field, a contact number field and an agent contact state identifier field;
the voice information acquisition unit is used for establishing connection with the contact corresponding to the connection instruction if the connection instruction of the contact is detected, and acquiring and storing voice information if the call is finished; and
the data recovery unit is used for writing the corresponding contact data into a recovery data table if the contact data with the seat contact state identifier field value of 0 is detected to exist in the contact list at a preset detection time point;
and the identification field setting unit is used for establishing connection with the contact corresponding to the connection instruction when the connection instruction of the contact is detected, and setting the value of the seat contact state identifier field in the data of the corresponding contact in the contact list to be 1 after the voice information is acquired and stored after the call is finished.
7. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the agent message alerting method of any one of claims 1 to 5 when executing the computer program.
8. A computer-readable storage medium, characterized in that the computer-readable storage medium stores a computer program which, when executed by a processor, causes the processor to carry out the agent message alerting method of any one of claims 1 to 5.
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Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2012003534A1 (en) * | 2010-07-05 | 2012-01-12 | Ipscape Pty Ltd | Call conversation manager |
| CN107864301A (en) * | 2017-10-26 | 2018-03-30 | 平安科技（深圳）有限公司 | Client's label management method, system, computer equipment and storage medium |
| CN109831592A (en) * | 2018-12-14 | 2019-05-31 | 深圳市佰仟金融服务有限公司 | A kind of list management method and list management equipment |
-
2019
- 2019-06-06 CN CN201910493449.9A patent/CN110351442B/en active Active
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2012003534A1 (en) * | 2010-07-05 | 2012-01-12 | Ipscape Pty Ltd | Call conversation manager |
| CN107864301A (en) * | 2017-10-26 | 2018-03-30 | 平安科技（深圳）有限公司 | Client's label management method, system, computer equipment and storage medium |
| CN109831592A (en) * | 2018-12-14 | 2019-05-31 | 深圳市佰仟金融服务有限公司 | A kind of list management method and list management equipment |
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