CN112887493A - User seat portrait based on call center data and matching method - Google Patents
User seat portrait based on call center data and matching method Download PDFInfo
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04M—TELEPHONIC COMMUNICATION
- 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
- H04M3/523—Centralised call answering arrangements requiring operator intervention, e.g. call or contact centers for telemarketing with call distribution or queueing
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04M—TELEPHONIC COMMUNICATION
- 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
- H04M3/523—Centralised call answering arrangements requiring operator intervention, e.g. call or contact centers for telemarketing with call distribution or queueing
- H04M3/5232—Call distribution algorithms
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Abstract
The invention discloses a user seat portrait based on call center data and a matching method, wherein a data acquisition module is used for acquiring user information and seat information; the data analysis module comprises a user analysis unit and an agent analysis unit, the user analysis unit is used for receiving user information and analyzing the user information to obtain user analysis information, the agent analysis unit is used for receiving the agent information and analyzing the agent information to obtain agent analysis information, and the user analysis information and the agent analysis information are sent to the data processing module; receiving and processing user analysis information and seat analysis information by using a data processing module to obtain processing set information, and sending the processing set information to an image matching module; receiving and processing the set information by using an image matching module and matching a user with an agent; the invention is used for solving the problem of poor effect of calling communication caused by incapability of portraying the user and the seat and dynamic matching.
Description
Technical Field
The invention relates to the technical field of data matching, in particular to a user seat portrait based on call center data and a matching method.
Background
The computer communication technology is usually utilized to process telephone requests from enterprises and customers, particularly has the capability of simultaneously processing a large number of incoming calls, also has calling number display, can automatically distribute incoming calls to personnel with corresponding skills for processing, and can record and store all incoming call information;
call centers typically first handle most customer queries or basic kinds of services; the main task of the call center will affect many important decisions regarding call center functionality, call handling measures, internal or external contact measures, and call center architecture, i.e. centralized or decentralized.
The existing call center carries out matching communication between the customer and the seat, and has the defects that: the problem of poor effect of call communication caused by the failure of portrait and dynamic matching of the user and the seat.
Disclosure of Invention
The invention aims to provide a user seat portrait based on call center data and a matching method, and the technical problems to be solved by the invention are as follows:
the problem that the effect of calling communication is poor due to the fact that users and seats cannot be portrait and dynamic matching cannot be conducted in the existing scheme is solved.
The purpose of the invention can be realized by the following technical scheme: the user seat portrait based on the call center data comprises a data acquisition module, a data analysis module, a data processing module and a portrait matching module;
the data acquisition module is used for acquiring user information and seat information, the user information comprises occupation data, position data, income data and arrearage data of a user, and the seat information comprises graduation data, employment data and reward and punishment data of a seat; sending the user information and the seat information to a data analysis module;
the data analysis module comprises a user analysis unit and an agent analysis unit, the user analysis unit is used for receiving user information and analyzing the user information to obtain user analysis information, the agent analysis unit is used for receiving the agent information and analyzing the agent information to obtain agent analysis information, and the user analysis information and the agent analysis information are sent to the data processing module;
the data processing module is used for receiving user analysis information and seat analysis information for processing to obtain user processing information and seat processing information, classifying and combining the user processing information and the seat processing information to obtain processing set information, and sending the processing set information to the portrait matching module, and the specific steps comprise:
s1: acquiring a collection-promoting division set in user analysis information and a processing sorting set in agent analysis information;
s2: acquiring users corresponding to the collection urging values in the collection urging division set and marking the users as users to be received, and acquiring seats corresponding to the processing values in the processing and sorting set and marking the seats as seats to be received;
s3: acquiring the reception time length and the reception times of the seat to be received and respectively marking the reception time length and the reception times as JS and JDC;
s4: obtaining the optimal value of the seat by using a formula, wherein the formula is as follows:
wherein Q isypExpressed as a superior value, b1 and b2 are expressed as preset different proportionality coefficients;
s5: carrying out ascending arrangement on the priority values, marking the seat corresponding to the priority value at the head of the rank as a matched seat, marking the seat corresponding to the priority value at the second rank as an alternative seat, and marking the seat corresponding to the priority value at the third rank as an emergency seat;
s6: classifying and combining the user to be received with the matched seat, the alternative seat and the emergency seat to obtain processing set information;
and the portrait matching module is used for receiving and processing the set information and matching the user with the seat.
Preferably, the user analysis unit is configured to receive the user information and analyze the user information to obtain user analysis information, and the specific steps include:
s21: acquiring occupation data, position data, income data and arrearage data in user information;
s22: setting different occupations to correspond to different occupational preset values, matching occupational data with all occupations to obtain corresponding occupational preset values, and marking the corresponding occupational preset values as ZWP; setting different positions to correspond to different position preset values, matching position data with all the positions to obtain corresponding position preset values, and marking the position preset values as ZYPs;
s23: acquiring a total annual income value and a mean monthly income value in income data, respectively marking the total annual income value and the mean monthly income value as NS and YS, acquiring a total arrearage amount and total arrearage times in arrearage data, marking the total arrearage amount as QZ and marking the total arrearage times as QC;
s24: normalizing the marked occupation preset value, position preset value, total annual income value, average monthly income value, total arrearage amount and total arrearage times, and taking values, and acquiring the collection urging value of the user information by using a formula, wherein the formula is as follows:
wherein Q iscsExpressed as a catalyst yield value, eta is expressed as a preset catalyst yield correction factor, and g1, g2, g3, g4 and g5 are expressed as preset different proportionality coefficients;
s25: performing descending arrangement on the catalytic recovery values to obtain a catalytic recovery arrangement set, and dividing the catalytic recovery arrangement set according to a preset division threshold to obtain a catalytic recovery division set;
s26: and classifying and combining the collection-urging partition set with the marked occupation preset value, position preset value, total annual income value, average monthly income value, total arrearage amount and total arrearage times to obtain user analysis information.
Preferably, the agent analysis unit is configured to receive the agent information and analyze the agent information to obtain the agent analysis information, and the specific steps include:
s31: obtaining graduation data, enrollment data and reward and punishment data in the seat information;
s32: setting different colleges to correspond to different college preset values, setting different specialties to correspond to different professional preset values, matching the colleges in the graduation data with all the colleges to obtain corresponding college preset values, and marking the corresponding college preset values as XY; matching graduation specialties in graduation data with all specialties to obtain corresponding professional preset values and marking the professional preset values as ZY;
s33: acquiring the attendance time and the attendance positions in the attendance data, marking the attendance time as RS, setting different seat positions to correspond to different preset seat positions, matching the attendance positions with all the seat positions to acquire corresponding preset seat positions and marking the corresponding preset seat positions as ZZ;
s34: acquiring reward times and punishment times in reward and punishment data, marking the reward times and punishment times as JC and FC respectively, and carrying out normalization processing and value taking on the marked college preset value, professional preset value, enrollment duration, sitting position preset value, reward times and punishment times;
s35: acquiring a processing value of the seat information by using a formula, wherein the formula is as follows:
wherein Q isclExpressed as a treatment value, mu is expressed as a preset treatment correction factor, and a1, a2 and a3 are expressed as preset different proportionality coefficients;
s36: performing descending order arrangement on the processing values to obtain a processing order set;
s37: and classifying and combining the processing sequencing set and the marked college preset value, professional preset value, time of admission, sitting position preset value, reward times and punishment times to obtain seat analysis information.
Preferably, the portrait matching module is configured to receive processing collection information and match a user with an agent, and the specific steps include:
s41: receiving and processing the set information and acquiring a user to be received, a matched seat, an alternative seat and an emergency seat;
s42: if only one user is simultaneously accessed, establishing connection and communication between the user to be accessed and the matched seat, acquiring communication duration and customer evaluation, setting different evaluations to correspond to one evaluation preset value, matching the customer evaluation with all the evaluations to acquire the corresponding evaluation preset values, and updating the portrait of the seat by using the evaluation preset values;
s43: after the communication is finished, adding one to the number of reception times of the matched seats, and accumulating and updating the communication duration and the reception duration;
s44: if two users to be received are simultaneously accessed, the two users to be received are randomly connected and communicated with the matched seat and the alternative seat, the communication time length and the customer evaluation are respectively obtained and marked as a first communication time length, a second communication time length, a first customer evaluation and a second customer evaluation, the first customer evaluation and the second customer evaluation are respectively matched with all the evaluations to obtain corresponding evaluation preset values, and the seat is subjected to portrait updating by utilizing the evaluation preset values;
s45: if the number of the users to be connected simultaneously exceeds two, dividing the ascending priority values into a group according to three, and sequentially marking the seats corresponding to the ascending priority values in the group as matched seats, alternative seats and emergency seats; and connecting and communicating the matched seats and the alternative seats in the groups with the users to be received respectively at random.
Preferably, the seat is portrait updated by using the evaluation preset value, and the method specifically comprises the following steps:
s51: marking the evaluation preset value as PY, and acquiring a superior value Q corresponding to the evaluation preset valueyp；
S52: obtaining the image value of the seat by using a formula, wherein the formula is as follows:
wherein Q ishxExpressed as image values, δ is expressed as a preset image correction factor, c1 and c2 are expressed as preset different scaling factors;
s53: and updating the seat information corresponding to the evaluation preset value by using the image value.
The matching method of the user seat portrait based on the call center data comprises the following specific steps:
the method comprises the following steps: collecting user information and seat information;
step two: marking and calculating the user information to obtain a collection urging value of the user information, and combining the collection urging value with marked data to obtain user analysis information;
step three: marking the seat information, calculating to obtain a processing value of the seat information, and combining the processing value with the marked data to obtain seat analysis information;
step four: analyzing and calculating the collection value and the processing value to obtain a preferred value of the seat, and matching the user with the seat by using the collection value and the preferred value;
step five: and acquiring the matched communication result and updating the portrait of the seat.
The invention has the beneficial effects that:
in various aspects disclosed by the invention, the data acquisition module is used for acquiring user information and seat information, wherein the user information comprises occupational data, position data, income data and arrearage data of a user, and the seat information comprises graduation data, employment data and reward and punishment data of a seat; sending the user information and the seat information to a data analysis module; by collecting and processing the user information and the seat information, effective data support is provided for the portrait and matching of the user and the seat;
the data analysis module comprises a user analysis unit and an agent analysis unit, the user analysis unit is used for receiving user information and analyzing the user information to obtain user analysis information, the agent analysis unit is used for receiving the agent information and analyzing the agent information to obtain agent analysis information, and the user analysis information and the agent analysis information are sent to the data processing module; by analyzing and portraying the user information and the seat information, the data between the user information and the seat information are linked, so that the user information and the seat information can be matched conveniently;
the data processing module is used for receiving and processing user analysis information and seat analysis information to obtain user processing information and seat processing information, classifying and combining the user processing information and the seat processing information to obtain processing set information, and sending the processing set information to the portrait matching module; by processing the user analysis information and the seat analysis information and establishing a connection, different users can dynamically match different seats, and the matching effect and the communication effect are improved;
receiving and processing the set information by using an image matching module and matching a user with an agent; by updating the portrait of the seat according to the last communication condition, the aims of portrait of the user and the seat and dynamic matching and improving the effect of calling communication can be achieved.
Drawings
The invention will be further described with reference to the accompanying drawings.
FIG. 1 is a block diagram of a user agent representation based on call center data in accordance with 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 only a part of the embodiments of the present invention, and not all of the embodiments. 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.
Example one
Referring to fig. 1, the present invention is a user seat portrait based on call center data, including a data acquisition module, a data analysis module, a data processing module and a portrait matching module;
the data acquisition module is used for acquiring user information and seat information, the user information comprises occupation data, position data, income data and arrearage data of a user, and the seat information comprises graduation data, employment data and reward and punishment data of a seat; sending the user information and the seat information to a data analysis module;
the data analysis module comprises a user analysis unit and an agent analysis unit, the user analysis unit is used for receiving user information and analyzing the user information to obtain user analysis information, and the specific steps comprise:
acquiring occupation data, position data, income data and arrearage data in user information;
setting different occupations to correspond to different occupational preset values, matching occupational data with all occupations to obtain corresponding occupational preset values, and marking the corresponding occupational preset values as ZWP; setting different positions to correspond to different position preset values, matching position data with all the positions to obtain corresponding position preset values, and marking the position preset values as ZYPs;
acquiring a total annual income value and a mean monthly income value in income data, respectively marking the total annual income value and the mean monthly income value as NS and YS, acquiring a total arrearage amount and total arrearage times in arrearage data, marking the total arrearage amount as QZ and marking the total arrearage times as QC;
normalizing the marked occupation preset value, position preset value, total annual income value, average monthly income value, total arrearage amount and total arrearage times, and taking values, and acquiring the collection urging value of the user information by using a formula, wherein the formula is as follows:
wherein Q iscsExpressed as a catalyst yield value, eta is expressed as a preset catalyst yield correction factor, and g1, g2, g3, g4 and g5 are expressed as preset different proportionality coefficients;
performing descending arrangement on the catalytic recovery values to obtain a catalytic recovery arrangement set, and dividing the catalytic recovery arrangement set according to a preset division threshold to obtain a catalytic recovery division set;
classifying and combining the collection-urging partition set with the marked occupation preset value, position preset value, total annual income value, average monthly income value, total arrearage amount and total arrearage times to obtain user analysis information;
the seat analysis unit is used for receiving the seat information and analyzing the seat information to obtain seat analysis information, and the specific steps comprise:
obtaining graduation data, enrollment data and reward and punishment data in the seat information;
setting different colleges to correspond to different college preset values, setting different specialties to correspond to different professional preset values, matching the colleges in the graduation data with all the colleges to obtain corresponding college preset values, and marking the corresponding college preset values as XY; matching graduation specialties in graduation data with all specialties to obtain corresponding professional preset values and marking the professional preset values as ZY;
acquiring the attendance time and the attendance positions in the attendance data, marking the attendance time as RS, setting different seat positions to correspond to different preset seat positions, matching the attendance positions with all the seat positions to acquire corresponding preset seat positions and marking the corresponding preset seat positions as ZZ;
acquiring reward times and punishment times in reward and punishment data, marking the reward times and punishment times as JC and FC respectively, and carrying out normalization processing and value taking on the marked college preset value, professional preset value, enrollment duration, sitting position preset value, reward times and punishment times;
acquiring a processing value of the seat information by using a formula, wherein the formula is as follows:
wherein Q isclExpressed as a treatment value, mu is expressed as a preset treatment correction factor, and a1, a2 and a3 are expressed as preset different proportionality coefficients;
performing descending order arrangement on the processing values to obtain a processing order set;
classifying and combining the processing sequencing set and the marked college preset value, professional preset value, job entry duration, sitting position preset value, reward times and punishment times to obtain seat analysis information;
sending the user analysis information and the agent analysis information to a data processing module;
the data processing module is used for receiving user analysis information and seat analysis information for processing to obtain user processing information and seat processing information, classifying and combining the user processing information and the seat processing information to obtain processing set information, and sending the processing set information to the portrait matching module, and the specific steps comprise:
s1: acquiring a collection-promoting division set in user analysis information and a processing sorting set in agent analysis information;
s2: acquiring users corresponding to the collection urging values in the collection urging division set and marking the users as users to be received, and acquiring seats corresponding to the processing values in the processing and sorting set and marking the seats as seats to be received;
s3: acquiring the reception time length and the reception times of the seat to be received and respectively marking the reception time length and the reception times as JS and JDC;
s4: obtaining the optimal value of the seat by using a formula, wherein the formula is as follows:
wherein Q isypExpressed as a superior value, b1 and b2 are expressed as preset different proportionality coefficients;
s5: carrying out ascending arrangement on the priority values, marking the seat corresponding to the priority value at the head of the rank as a matched seat, marking the seat corresponding to the priority value at the second rank as an alternative seat, and marking the seat corresponding to the priority value at the third rank as an emergency seat;
s6: classifying and combining the user to be received with the matched seat, the alternative seat and the emergency seat to obtain processing set information;
the portrait matching module is used for receiving and processing the collection information and matching the user with the seat, and the specific steps comprise:
receiving and processing the set information and acquiring a user to be received, a matched seat, an alternative seat and an emergency seat;
if only one user is simultaneously accessed, establishing connection and communication between the user to be accessed and the matched seat, acquiring communication duration and customer evaluation, setting different evaluations to correspond to one evaluation preset value, matching the customer evaluation with all the evaluations to acquire the corresponding evaluation preset values, and updating the portrait of the seat by using the evaluation preset values; the method comprises the following specific steps:
marking the evaluation preset value as PY, and acquiring a superior value Q corresponding to the evaluation preset valueyp；
Obtaining the image value of the seat by using a formula, wherein the formula is as follows:
wherein Q ishxExpressed as image values, δ is expressed as a preset image correction factor, c1 and c2 are expressed as preset different scaling factors;
updating the seat information corresponding to the evaluation preset value by using the image value;
after the communication is finished, adding one to the number of reception times of the matched seats, and accumulating and updating the communication duration and the reception duration;
if two users to be received are simultaneously accessed, the two users to be received are randomly connected and communicated with the matched seat and the alternative seat, the communication time length and the customer evaluation are respectively obtained and marked as a first communication time length, a second communication time length, a first customer evaluation and a second customer evaluation, the first customer evaluation and the second customer evaluation are respectively matched with all the evaluations to obtain corresponding evaluation preset values, and the seat is subjected to portrait updating by utilizing the evaluation preset values;
if the number of the users to be connected simultaneously exceeds two, dividing the ascending priority values into a group according to three, and sequentially marking the seats corresponding to the ascending priority values in the group as matched seats, alternative seats and emergency seats; and connecting and communicating the matched seats and the alternative seats in the groups with the users to be received respectively at random.
Example two
The matching method of the user seat portrait based on the call center data comprises the following specific steps:
the method comprises the following steps: collecting user information and seat information;
step two: marking and calculating the user information to obtain a collection urging value of the user information, and combining the collection urging value with marked data to obtain user analysis information;
step three: marking the seat information, calculating to obtain a processing value of the seat information, and combining the processing value with the marked data to obtain seat analysis information;
step four: analyzing and calculating the collection value and the processing value to obtain a preferred value of the seat, and matching the user with the seat by using the collection value and the preferred value;
step five: and acquiring the matched communication result and updating the portrait of the seat.
The working principle of the invention is as follows: in the embodiment of the invention, a data acquisition module is used for acquiring user information and seat information, wherein the user information comprises occupational data, position data, income data and arrearage data of a user, and the seat information comprises graduation data, employment data and reward and punishment data of a seat; sending the user information and the seat information to a data analysis module; by collecting and processing the user information and the seat information, effective data support is provided for the portrait and matching of the user and the seat;
the data analysis module comprises a user analysis unit and an agent analysis unit, and the user analysis unit is used for receiving user information for analysis and a formula is used for analysis
classifying and combining the processing sequencing set and the marked college preset value, professional preset value, time of entry, sitting position preset value, reward times and punishment times to obtain seat analysis information, and sending the user analysis information and the seat analysis information to a data processing module; by analyzing and portraying the user information and the seat information, the data between the user information and the seat information are linked, so that the user information and the seat information can be matched conveniently;
receiving and processing the user analysis information and the seat analysis information by using a data processing module to obtain user processing information and seat processing information, classifying and combining the user processing information and the seat processing information, and using a formula
Acquiring a superior value of the seat, performing ascending arrangement on the superior value, marking the seat corresponding to the superior value at the head of the seat as a matched seat, marking the seat corresponding to the superior value at the second position as an alternative seat, and marking the seat corresponding to the superior value at the third position as an emergency seat; classifying and combining the user to be received with the matched seat, the alternative seat and the emergency seat to obtain processing set information, and sending the processing set information to the portrait matching module; by processing the user analysis information and the seat analysis information and establishing a connection, different users can dynamically match different seats, and the matching effect and the communication effect are improved;
receiving and processing the information of the set by using an image matching module, matching the user with the seat by using a formula
Acquiring an image value of a seat; updating the seat information corresponding to the evaluation preset value by using the image value; by updating the portrait of the seat according to the last communication condition, the aims of portrait of the user and the seat and dynamic matching and improving the effect of calling communication can be achieved.
In the embodiments provided by the present invention, it should be understood that the disclosed system and method can be implemented in other ways. For example, the above-described embodiments are merely illustrative, and for example, the division of the modules is only one logical functional division, and other divisions may be realized in practice.
The modules described as separate parts may or may not be physically separate, and parts displayed as modules may or may not be physical modules, may be located in one place, or may be distributed on a plurality of network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the method of the embodiment.
In addition, each functional module in each embodiment of the present invention may be integrated into one control module, or each module may exist alone physically, or two or more modules may be integrated into one module. The integrated module can be realized in a hardware form, and can also be realized in a form of hardware and a software functional module.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential attributes thereof.
The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference signs in the claims shall not be construed as limiting the claim concerned.
Furthermore, it is to be understood that the word "comprising" does not exclude other modules or steps, and the singular does not exclude the plural. A plurality of modules or means recited in the system claims may also be implemented by one module or means in software or hardware. The terms second, etc. are used to denote names, but not any particular order.
Finally, it should be noted that the above examples are only intended to illustrate the technical process of the present invention and not to limit the same, and although the present invention has been described in detail with reference to the preferred embodiments, it will be understood by those skilled in the art that modifications or equivalent substitutions may be made to the technical process of the present invention without departing from the spirit and scope of the technical process of the present invention.
Claims (6)
1. The user seat portrait based on the call center data is characterized by comprising a data acquisition module, a data analysis module, a data processing module and a portrait matching module;
the data acquisition module is used for acquiring user information and seat information, the user information comprises occupation data, position data, income data and arrearage data of a user, and the seat information comprises graduation data, employment data and reward and punishment data of a seat; sending the user information and the seat information to a data analysis module;
the data analysis module comprises a user analysis unit and an agent analysis unit, the user analysis unit is used for receiving user information and analyzing the user information to obtain user analysis information, the agent analysis unit is used for receiving the agent information and analyzing the agent information to obtain agent analysis information, and the user analysis information and the agent analysis information are sent to the data processing module;
the data processing module is used for receiving user analysis information and seat analysis information for processing to obtain user processing information and seat processing information, classifying and combining the user processing information and the seat processing information to obtain processing set information, and sending the processing set information to the portrait matching module, and the specific steps comprise:
s1: acquiring a collection-promoting division set in user analysis information and a processing sorting set in agent analysis information;
s2: acquiring users corresponding to the collection urging values in the collection urging division set and marking the users as users to be received, and acquiring seats corresponding to the processing values in the processing and sorting set and marking the seats as seats to be received;
s3: acquiring the reception time length and the reception times of the seat to be received and respectively marking the reception time length and the reception times as JS and JDC;
s4: obtaining the optimal value of the seat by using a formula, wherein the formula is as follows:
wherein Q isypExpressed as a superior value, b1 and b2 are expressed as preset different proportionality coefficients;
s5: carrying out ascending arrangement on the priority values, marking the seat corresponding to the priority value at the head of the rank as a matched seat, marking the seat corresponding to the priority value at the second rank as an alternative seat, and marking the seat corresponding to the priority value at the third rank as an emergency seat;
s6: classifying and combining the user to be received with the matched seat, the alternative seat and the emergency seat to obtain processing set information;
and the portrait matching module is used for receiving and processing the set information and matching the user with the seat.
2. The call center data based user agent representation as recited in claim 1, wherein the user analysis unit is configured to receive user information and analyze the user information to obtain user analysis information, and the specific steps comprise:
s21: acquiring occupation data, position data, income data and arrearage data in user information;
s22: setting different occupations to correspond to different occupational preset values, matching occupational data with all occupations to obtain corresponding occupational preset values, and marking the corresponding occupational preset values as ZWP; setting different positions to correspond to different position preset values, matching position data with all the positions to obtain corresponding position preset values, and marking the position preset values as ZYPs;
s23: acquiring a total annual income value and a mean monthly income value in income data, respectively marking the total annual income value and the mean monthly income value as NS and YS, acquiring a total arrearage amount and total arrearage times in arrearage data, marking the total arrearage amount as QZ and marking the total arrearage times as QC;
s24: normalizing the marked occupation preset value, position preset value, total annual income value, average monthly income value, total arrearage amount and total arrearage times, and taking values, and acquiring the collection urging value of the user information by using a formula, wherein the formula is as follows:
wherein Q iscsExpressed as a catalyst yield value, eta is expressed as a preset catalyst yield correction factor, and g1, g2, g3, g4 and g5 are expressed as preset different proportionality coefficients;
s25: performing descending arrangement on the catalytic recovery values to obtain a catalytic recovery arrangement set, and dividing the catalytic recovery arrangement set according to a preset division threshold to obtain a catalytic recovery division set;
s26: and classifying and combining the collection-urging partition set with the marked occupation preset value, position preset value, total annual income value, average monthly income value, total arrearage amount and total arrearage times to obtain user analysis information.
3. The user agent representation based on call center data as claimed in claim 1, wherein the agent analysis unit is configured to receive the agent information and analyze the agent information to obtain the agent analysis information, and the specific steps include:
s31: obtaining graduation data, enrollment data and reward and punishment data in the seat information;
s32: setting different colleges to correspond to different college preset values, setting different specialties to correspond to different professional preset values, matching the colleges in the graduation data with all the colleges to obtain corresponding college preset values, and marking the corresponding college preset values as XY; matching graduation specialties in graduation data with all specialties to obtain corresponding professional preset values and marking the professional preset values as ZY;
s33: acquiring the attendance time and the attendance positions in the attendance data, marking the attendance time as RS, setting different seat positions to correspond to different preset seat positions, matching the attendance positions with all the seat positions to acquire corresponding preset seat positions and marking the corresponding preset seat positions as ZZ;
s34: acquiring reward times and punishment times in reward and punishment data, marking the reward times and punishment times as JC and FC respectively, and carrying out normalization processing and value taking on the marked college preset value, professional preset value, enrollment duration, sitting position preset value, reward times and punishment times;
s35: acquiring a processing value of the seat information by using a formula, wherein the formula is as follows:
wherein Q isclExpressed as a treatment value, mu is expressed as a preset treatment correction factor, and a1, a2 and a3 are expressed as preset different proportionality coefficients;
s36: performing descending order arrangement on the processing values to obtain a processing order set;
s37: and classifying and combining the processing sequencing set and the marked college preset value, professional preset value, time of admission, sitting position preset value, reward times and punishment times to obtain seat analysis information.
4. The call center data based user agent profile of claim 1, wherein the profile matching module is configured to receive process aggregated information and match users with agents, and the specific steps comprise:
s41: receiving and processing the set information and acquiring a user to be received, a matched seat, an alternative seat and an emergency seat;
s42: if only one user is simultaneously accessed, establishing connection and communication between the user to be accessed and the matched seat, acquiring communication duration and customer evaluation, setting different evaluations to correspond to one evaluation preset value, matching the customer evaluation with all the evaluations to acquire the corresponding evaluation preset values, and updating the portrait of the seat by using the evaluation preset values;
s43: after the communication is finished, adding one to the number of reception times of the matched seats, and accumulating and updating the communication duration and the reception duration;
s44: if two users to be received are simultaneously accessed, the two users to be received are randomly connected and communicated with the matched seat and the alternative seat, the communication time length and the customer evaluation are respectively obtained and marked as a first communication time length, a second communication time length, a first customer evaluation and a second customer evaluation, the first customer evaluation and the second customer evaluation are respectively matched with all the evaluations to obtain corresponding evaluation preset values, and the seat is subjected to portrait updating by utilizing the evaluation preset values;
s45: if the number of the users to be connected simultaneously exceeds two, dividing the ascending priority values into a group according to three, and sequentially marking the seats corresponding to the ascending priority values in the group as matched seats, alternative seats and emergency seats; and connecting and communicating the matched seats and the alternative seats in the groups with the users to be received respectively at random.
5. The call center data based user agent profile of claim 4, wherein the profile update of the agent is performed using a pre-evaluated value, and the method comprises the steps of:
s51: marking the evaluation preset value as PY, and acquiring a superior value Q corresponding to the evaluation preset valueyp；
S52: obtaining the image value of the seat by using a formula, wherein the formula is as follows:
wherein Q ishxExpressed as image values, δ is expressed as a preset image correction factor, c1 and c2 are expressed as preset different scaling factors;
s53: and updating the seat information corresponding to the evaluation preset value by using the image value.
6. The matching method of the user seat portrait based on the call center data is characterized in that the matching method comprises the following specific steps:
the method comprises the following steps: collecting user information and seat information;
step two: marking and calculating the user information to obtain a collection urging value of the user information, and combining the collection urging value with marked data to obtain user analysis information;
step three: marking the seat information, calculating to obtain a processing value of the seat information, and combining the processing value with the marked data to obtain seat analysis information;
step four: analyzing and calculating the collection value and the processing value to obtain a preferred value of the seat, and matching the user with the seat by using the collection value and the preferred value;
step five: and acquiring the matched communication result and updating the portrait of the seat.
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| CN107590588A (en) * | 2017-08-24 | 2018-01-16 | 平安科技（深圳）有限公司 | Method for allocating tasks, device and computer-readable recording medium |
| CN107872593A (en) * | 2017-03-13 | 2018-04-03 | 平安科技（深圳）有限公司 | Attend a banquet the method and device of distribution |
| CN108391022A (en) * | 2018-02-13 | 2018-08-10 | 平安科技（深圳）有限公司 | A kind of call processing method, electronic device and computer readable storage medium |
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Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107872593A (en) * | 2017-03-13 | 2018-04-03 | 平安科技（深圳）有限公司 | Attend a banquet the method and device of distribution |
| CN107590588A (en) * | 2017-08-24 | 2018-01-16 | 平安科技（深圳）有限公司 | Method for allocating tasks, device and computer-readable recording medium |
| CN108391022A (en) * | 2018-02-13 | 2018-08-10 | 平安科技（深圳）有限公司 | A kind of call processing method, electronic device and computer readable storage medium |
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