CN113344600A - Thread data processing method, thread data processing device, storage medium and thread middle station - Google Patents
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Abstract
The invention discloses a method and a device for processing thread data, a storage medium and a thread middle station, and relates to the technical field of computer information processing. The method comprises the following steps: collecting clue data and/or event data of each service line; preprocessing the clue data and/or the event data to obtain clue tag values corresponding to the clue data and/or the event data, and storing the clue tag values in corresponding user portrait; carrying out layering processing on the user portrait according to the clue label value through a pre-trained layering algorithm model to obtain a layering result of the user portrait; and according to a preset clue distribution strategy, distributing clue data/or event data corresponding to the user portrait to a corresponding consumption service line according to the layering result of the user portrait. The method can finely and reasonably distribute the user portrait, so that the clue distribution can be suitable for a multi-service line distribution scene, and the optimal life cycle total value of clue data is effectively improved.
Description
Technical Field
The invention relates to the technical field of computer information processing, in particular to a method and a device for processing cable data, a storage medium, computer equipment and a cable relay station.
Background
Clue data is the most basic and important element in a Customer relationship management system (CRM), and in brief, clue data is Customer data collected by an enterprise through various channels. The customer relationship management system is an information system for collecting, managing and analyzing customer data established for enterprises by using software, hardware and network technologies. The customer relationship management system takes clue data management as a core, records various interactive behaviors of the enterprise and customers in the marketing and sales processes and states of various related activities, provides various data models, and can provide powerful support for later data analysis and enterprise decision.
In the prior art, a customer relationship management system generally feeds thread data through an upstream channel, then performs unified management and operation inside the system, and then manually puts the thread data into a single service line, or manually selects and acquires the thread data by service line personnel, and finally the service line personnel touch the thread data and provide customer service for customers.
However, the above scheme usually has a rough way to process clue data. For example, the ranking of the thread data is often dependent on only a single action of the client or limited by the personal experience of the decision maker, so that it is difficult to extract the thread value suitable for the service line in the thread data. Moreover, even if the classification of a thread is applied to a certain service line, when the classification of a thread is applied to a plurality of service lines at the same time, the classification of a thread is not common due to the difference in the form of each service line and the difference in the target of each service line. In addition, under the condition of multiple service lines, each service line needs to repeatedly develop the thread distribution tool and make a personalized distribution strategy, so that the thread distribution tools of each service line can only be maintained respectively, and the efficiency is very low. Based on the above problems, the existing customer relationship management system is difficult to be applied to a multi-service line thread distribution scene, and the existing thread data processing mode cannot meet the expected actual requirements of customers in time.
Disclosure of Invention
In view of the above, the present application provides a method, an apparatus, a storage medium, a computer device, and a thread center station for processing thread data, and mainly aims to solve the technical problems that the existing thread data is not accurate in classification and thread distribution cannot be applied to multiple service lines.
According to a first aspect of the present invention, there is provided a method for processing data of a wire, the method comprising:
collecting clue data and/or event data of each service line;
preprocessing the clue data and/or the event data to obtain clue tag values corresponding to the clue data and/or the event data, and storing the clue tag values in corresponding user portrait;
carrying out layering processing on the user portrait according to the clue label value through a pre-trained layering algorithm model to obtain a layering result of the user portrait;
and according to a preset clue distribution strategy, distributing clue data/or event data corresponding to the user portrait to a corresponding consumption service line according to the layering result of the user portrait.
According to a second aspect of the present invention, there is provided a data processing apparatus for processing data of a wire, the apparatus comprising:
the clue acquisition module is used for acquiring clue data and/or event data supplied to each service line;
the clue preprocessing module is used for preprocessing the clue data and/or the event data to obtain clue tag values corresponding to the clue data and/or the event data and storing the clue tag values in the corresponding user portrait;
the clue layering module is used for carrying out layering processing on the user portrait according to the clue label value through a pre-trained layering algorithm model to obtain a layering result of the user portrait;
and the clue distribution module is used for distributing clue data/event data corresponding to the user portrait to the corresponding consumption service line according to a preset clue distribution strategy and the layering result of the user portrait.
According to a third aspect of the present invention, there is provided a cable station comprising an interface layer and a service processing layer, wherein,
the interface layer is used for acquiring clue data and/or event data of each service line;
the business processing layer is used for preprocessing the thread data and/or the event data to obtain thread tag values corresponding to the thread data and/or the event data and storing the thread tag values in corresponding user portraits;
the business processing layer is also used for carrying out layering processing on the user portrait according to the clue label value through a pre-trained layering algorithm model to obtain a layering result of the user portrait;
and the interface layer is also used for distributing the clue data/or the event data corresponding to the user portrait to the corresponding consumption service line according to a preset clue distribution strategy and the layering result of the user portrait.
According to a fourth aspect of the present invention, there is provided a storage medium having stored thereon a computer program which, when executed by a processor, implements the above-described method of processing cue data.
According to a fifth aspect of the present invention, there is provided a computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the above mentioned processing method of cue data when executing the program.
The invention provides a processing method, a device, a storage medium, computer equipment and a clue center station of clue data, which are used for acquiring clue data and/or event data supplied to a service line, preprocessing the acquired clue data and/or event data to obtain clue label values corresponding to the clue data and/or event data, storing the clue label values in corresponding user portraits, layering the user portraits according to the clue label values through a pre-trained layering algorithm model to obtain layering results of the user portraits, and distributing the clue data and/or event data corresponding to the user portraits to corresponding consumption service lines according to the layering results of the user portraits by a preset clue distribution strategy. According to the method, clue information can be enriched by collecting clue data and/or event data supplied to the service lines, and user portrait information can be constructed and enriched by performing tagging processing on the clue data and/or event data, so that the user portrait can be finely layered and reasonably distributed, clue distribution can be suitable for a multi-service line distribution scene, and the accuracy of clue data distribution is effectively improved. In addition, the method effectively avoids the problem of repeated development of a plurality of service lines by providing a unified collection, management and distribution mode of the clue data, improves the processing efficiency of the clue data and reduces the development and maintenance cost of the clue data processing system.
The foregoing description is only an overview of the technical solutions of the present application, and the present application can be implemented according to the content of the description in order to make the technical means of the present application more clearly understood, and the following detailed description of the present application is given in order to make the above and other objects, features, and advantages of the present application more clearly understandable.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the invention and together with the description serve to explain the invention without limiting the invention. In the drawings:
FIG. 1 is a flow chart of a method for processing string data according to an embodiment of the present invention;
FIG. 2 is a flow chart of a method for processing string data according to an embodiment of the present invention;
fig. 3 is an application scenario diagram illustrating a processing method of cable data according to an embodiment of the present invention;
fig. 4 is an application scenario diagram illustrating a processing method of cable data according to an embodiment of the present invention;
fig. 5 is an application scenario diagram illustrating a processing method of cable data according to an embodiment of the present invention;
fig. 6 is an application scenario diagram illustrating a processing method of cable data according to an embodiment of the present invention;
FIG. 7 is a schematic structural diagram of a device for processing data of a cable according to an embodiment of the present invention;
fig. 8 is a schematic structural diagram of a cable center console according to an embodiment of the present invention.
Detailed Description
The invention will be described in detail hereinafter with reference to the accompanying drawings in conjunction with embodiments. It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict.
In one embodiment, as shown in fig. 1, a method for processing data of a cable is provided, which is described by taking the method as an example of being applied to a computer device such as a server, and includes the following steps:
101. thread data and/or event data for each service line is collected.
The service line supply refers to a channel for acquiring clue data and/or event data, such as an application program, a community, a platform and the like; clue data refers to user data collected through various channels, such as "user a, gender maid, age 30", and the like; the event data refers to data generated by the triggering of the clue behavior of the user and describes the action of the clue in a certain time and scene, such as "user A watches the live broadcast of a certain platform in the afternoon of a certain day" and the like.
Specifically, the computer device may receive, via the unified interface, the thread data and/or the event data for each service line. For example, the computer device may actively pull the thread data and/or event data provided for the self-processing on the service line, or may process the service data into the thread data and/or event data by collecting the service data. It should be noted that the clue data and/or event data acquired by the computer device are acquired without infringing the user's rights and permission, for example, the clue data may be user information actively filled by the user when registering the application software, the event data may be user information acquired by the authorization platform when the user participates in the activity, and the like. It will be appreciated that the method is equally applicable whether the service line is one or more. Moreover, the cue data and the event data may be collected simultaneously or separately, and this embodiment is not limited in this respect.
102. And preprocessing the clue data and/or the event data to obtain clue tag values corresponding to the clue data and/or the event data, and storing the clue tag values in the corresponding user portrait.
The data preprocessing refers to a process of uniformly processing the clue data and/or event data of each channel so as to process the clue data and/or event data into a data form which can be identified and processed by computer equipment; thread tags refer to abstract classifications and generalizations describing the attributes and characteristics of a thread, with classifiability, such as age, gender, and so forth; the cue tag value refers to a specific value of the cue tag, such as "age 30", "gender women", etc.; a user representation refers to a user model formed of at least one cue tag value organized together based on cue data and/or event data, which may be continually updated and enriched as cue tag values are continually changing or cumulative.
In this embodiment, the computer device may preprocess the thread data and/or the event data, so as to process the collected thread data and/or event data into one or more thread tag values, and store each thread tag value in the user representation corresponding to each thread. For example, the computer device may preprocess the cue data "user a, gender maid, age 30" into two cue tag values of "gender maid" and "age 30", and then save the two cue tag values of "gender maid" and "age 30" into the user representation corresponding to "user a" so that "gender maid" and "age 30" become the two cue tag values of "user a". For another example, the computer device may pre-process the event data "user a watched a live broadcast of a certain platform in the afternoon of a certain day" into a clue tag "watched a live broadcast of a certain platform in the afternoon of a certain day", and then store the clue tag "watched a live broadcast in the afternoon of a certain day" into the user portrait corresponding to "user a", thereby enriching the user portrait of "user a".
In this embodiment, the hint tag corresponding to the hint tag value can be pre-stored in the computer device. For example, the computer device may store each cue tag in the form of a cue tag template, and then compare and match the cue data and/or event data with the cue tag template during preprocessing, thereby filtering out satisfactory cue tag values for storage in the corresponding user representation. In addition, the clue notepad can be added or deleted at any time. In this way, the computing device can focus computing resources on the more valuable cue data, while other data outside the cue tags can be discarded or stored on other computing devices.
103. And carrying out layering processing on the user portrait according to the clue label value through a pre-trained layering algorithm model to obtain a layering result of the user portrait.
The user portrait layering refers to the matching degree between the user and each service target under different service forms, which is derived based on each clue label value of the user portrait. In the present embodiment, the hierarchical algorithm model may include a pre-trained hierarchical algorithm model or/and a pre-set hierarchical rule, and the like. Specifically, when the user portrait is layered, each clue label value of the user portrait can be respectively matched with each preset layering rule, and/or each clue label value is respectively input into a pre-trained layering algorithm model, so that a layering result of the user portrait is obtained. It is understood that the user representation may be layered at regular time intervals or at any time in response to a user request, and that the layered result of the user representation may be changed at any time as the user representation is continuously updated or enriched, or may be stored as a cue tag value in the corresponding user representation.
In this embodiment, the hierarchical result of the user representation may include a consumption service line corresponding to the user representation and a cue matching degree between the user representation and each consumption service line, where the cue matching degree may be expressed by a hierarchical level, for example, a higher hierarchical level represents a higher cue matching degree; the lower the hierarchical level, the lower the representative cue match. In addition, the hierarchical level of the user representation may vary for different consumption business lines, for example, the hierarchical result of the user representation for "user a" is: "the hierarchical level for the consumption service line a is high", "the hierarchical level for the consumption service line B is medium", and "the hierarchical level for the consumption service line C is low". According to the embodiment, through the layering result of the user portrait, the clue matching relationship between each user portrait and each consumption service line can be determined, so that powerful basis is provided for issuing subsequent clues.
104. And according to a preset clue distribution strategy, distributing clue data/or event data corresponding to the user portrait to a corresponding consumption service line according to the layering result of the user portrait.
The thread distribution policy refers to some thread distribution mechanisms set based on the hierarchical result of the user portrait, including but not limited to thread issuing modes (such as timed issuing or real-time issuing), consumption service line competition rules (competition and cooperation relationship of each consumption service line), thread recycling identifiers, distribution priorities of each consumption service line and distribution quantity of each consumption service line, and the like.
In this embodiment, when issuing thread data and/or event data, the thread distribution policy and the hierarchical result of the user representation may cooperate with each other, that is, when issuing a thread, the thread data and/or the event data is issued to a consuming service line with a high thread matching degree according to a thread matching relationship between the user representation and the consuming service line, and then, a competing relationship, a priority and a distribution number of the consuming service lines in the thread distribution policy are considered, so that thread data and/or event data with a high thread matching degree, a non-conflicting competing relationship and a proper number are distributed to different consuming service lines. In addition, the delivered thread data and/or event data can be selected and matched in a targeted manner according to different consumption service lines, for example, for the consumption service line a, the delivered thread data may be "user B, gender, woman, age 30, accumulated 500 yuan consumed on the consumption service line a in nearly 7 days, and the hierarchical level for the consumption service line a is high".
Specifically, the computer device may sequentially distribute, according to the preset cue distribution policy, the cue data and/or the event data corresponding to the user representation to each consumption business line according to the layering result of the user representation, so that business personnel of the corresponding consumption business line may perform targeted service on the client according to the distributed cue data and/or event data. It should be noted that, the consumption service line may overlap with the supply service line, and the consumption service line may be one or more, when the consumption service line is multiple, the layering result of the user representation may indicate the matching degree between the cue data and each consumption service line, so that each cue data and/or event data can be distributed to the appropriate consumption service line to improve the best life cycle total value of the cue data (best life time value).
According to the processing method of the clue data, clue information is enriched by collecting a plurality of clue data and/or event data supplied to the service lines, labeling processing is performed on the clue data and/or event data, user portrait information is constructed and enriched, and then fine layering and reasonable distribution are performed on the user portrait, so that clue distribution can be suitable for a multi-service line distribution scene, and accuracy of clue data distribution is effectively improved. In addition, the unified collection, management and distribution mode of the clue data provided by the method effectively avoids the problem of repeated development of a plurality of service lines, improves the processing efficiency of the clue data, and reduces the development and maintenance cost of the clue data processing system.
Further, as a refinement and an extension of the specific implementation of the above embodiment, in order to fully illustrate the implementation process of the embodiment, a method for processing clue data is provided, as shown in fig. 2, the method includes the following steps:
201. thread data and/or event data for each service line is collected.
Specifically, the computer device may receive, via the unified interface, the thread data and/or the event data for each service line. The clue data and/or the event data are collected under the condition that the user rights and interests are not violated and the user permission is obtained, for example, the clue data can be user information actively filled by the user when the user registers the application software, the event data can be user information acquired by an authorization platform when the user participates in the activity, and the like. It will be appreciated that the method is equally applicable whether the service line is one or more. Moreover, the cue data and the event data may be collected simultaneously or separately, and this embodiment is not limited in this respect.
In an alternative embodiment, the collection of cue data and/or event data may be accomplished by: respectively acquiring lead data to be put in storage and buried data of each service line by using a lead acquisition tool and a data stream acquisition tool (such as a Flink tool) to obtain lead data and/or event data of each service line, and/or pulling the service data of each service line, and processing the service data to obtain the lead data and/or event data of each service line. In this embodiment, the two thread collection methods do not conflict with each other, and therefore can be performed simultaneously or separately. Through the data acquisition mode, the computer equipment can acquire rich clue data and/or event data, including big data buried point data, service data, self-processing clue data and the like supplied to the service line, so that clue labels can be screened out from the clue data and/or the event data to enrich the user model, and the layering accuracy of the user model can be improved.
202. And preprocessing the clue data and/or the event data to obtain clue tag values corresponding to the clue data and/or the event data, and storing the clue tag values in the corresponding user portrait.
Specifically, the computer device may preprocess the thread data and/or the event data, thereby processing the collected thread data and/or event data into one or more thread tag values, and storing each thread tag value in a user representation corresponding to each thread. For example, the computer device may preprocess the cue data "user a, gender maid, age 30" into two cue tag values of "gender maid" and "age 30", and then save the two cue tag values of "gender maid" and "age 30" into the user representation corresponding to "user a" so that "gender maid" and "age 30" become the two cue tag values of "user a". For another example, the computer device may pre-process the event data "user a watched a live broadcast of a certain platform in the afternoon of a certain day" into a clue tag "watched a live broadcast of a certain platform in the afternoon of a certain day", and then store the clue tag "watched a live broadcast in the afternoon of a certain day" into the user portrait corresponding to "user a", thereby enriching the user portrait of "user a".
In an alternative embodiment, preprocessing the cable data and/or event data may be implemented by: the method comprises the steps of firstly comparing clue data and/or event data with a preset clue tag value template to screen out clue tags and clue tag values corresponding to the clue data and/or event data, then finding user images corresponding to the clue data and/or event data according to identification information carried in the clue data and/or event data, and finally storing the clue tag values corresponding to the clue data and/or event data in the user images corresponding to the clue data and/or event data. In this way, the computing device can focus computing resources on the more valuable cue data, while other data outside the cue tags can be discarded or stored on other computing devices.
203. And inquiring the clue value corresponding to the user image according to the clue tag value, and storing the clue value corresponding to the user image in the corresponding user image in the form of the clue tag value.
Specifically, after filtering out the cue tag values in the cue data and/or the event data, the computer device may further query the cue value corresponding to the user image, where the cue value corresponding to the user image may be expressed by recent data of the user, for example, the cue value corresponding to the user image may be "total amount of consumed amount of the business line a in the last 7 days" or "total amount of consumed amount of the business line B in the last 14 days" or the like. In this embodiment, the computer device may utilize a value query tool (e.g., a clue sandbox tool) to query a clue value corresponding to the user portrait according to the clue tag value, and then maintain the clue value corresponding to the user portrait in the form of the clue tag value, so that the clue value may be utilized to accurately measure the clue matching degree between the user portrait and each consumption service line when performing subsequent layering processing on the user portrait.
In this embodiment, the method for obtaining the cue value of the user portrait may be implemented by first obtaining a query request of the user portrait, where the query request of the user portrait carries at least one cue tag value, then querying at least one user portrait and a cue value corresponding to each of the at least one user portrait according to the at least one cue tag value, and finally storing the cue value corresponding to each of the at least one user portrait in the corresponding user portrait in the form of the cue tag value.
204. And carrying out layering processing on the user portrait according to the clue label value through a pre-trained layering algorithm model to obtain a layering result of the user portrait.
Specifically, the hierarchical algorithm model may include a pre-trained hierarchical algorithm model or/and a pre-set hierarchical rule, and the like. Specifically, when the user portrait is layered, each clue label value of the user portrait can be respectively matched with each preset layering rule, and/or each clue label value is respectively input into a pre-trained layering algorithm model, so that a layering result of the user portrait is obtained. It will be appreciated that the user representation layering process may be performed periodically or at any time in response to a user request, and that the user representation layering results may change at any time as the user representation is continually updated or enriched.
In an alternative embodiment, the layering of the user representation may be performed by: firstly, sequentially inputting all clue label values corresponding to the user portrait into a pre-trained layering algorithm model to obtain a layering result of the user portrait, and then storing the layering result of the user portrait in a clue label value mode to enrich the user portrait. In this embodiment, the results of layering the user representation may include a consumption business line corresponding to the user representation and a degree of thread matching between the user representation and the consumption business line. Wherein, the thread matching degree can be expressed by hierarchical level, for example, the higher the hierarchical level is, the higher the representative thread matching degree is; the lower the hierarchical level, the lower the representative cue match. In addition, the hierarchical level of the user representation may vary for different consumption business lines, for example, the hierarchical result of the user representation for "user a" is: "the hierarchical level for the consumption service line a is high", "the hierarchical level for the consumption service line B is medium", and "the hierarchical level for the consumption service line C is low". Through the layering result of the user portrait, the clue matching relationship between each user portrait and each consumption service line can be clarified, so that powerful basis is provided for issuing subsequent clues.
205. And according to a preset clue distribution strategy, distributing clue data/or event data corresponding to the user portrait to a corresponding consumption service line according to the layering result of the user portrait.
Specifically, the thread distribution policy includes, but is not limited to, a thread issuing manner (e.g., timed issuing or real-time issuing), a consumption service line competition rule (competition and cooperation relationship of each consumption service line), a thread recovery identifier, a distribution priority of each consumption service line, a distribution quantity of each consumption service line, and the like. Specifically, the computer device may sequentially distribute, according to the preset cue distribution policy, the cue data and/or the event data corresponding to the user representation to each consumption business line according to the layering result of the user representation, so that business personnel of the corresponding consumption business line may perform targeted service on the client according to the distributed cue data and/or event data.
In an alternative embodiment, the distribution of the cable may be achieved by: firstly, determining a consumption service line corresponding to the user portrait and a thread matching degree between the user portrait and each consumption service line according to a layering result of the user portrait, and then distributing thread data/or event data corresponding to the user portrait to the consumption service line corresponding to the user portrait in a message form according to a thread distribution strategy and the thread matching degree between the user portrait and each consumption service line. In this embodiment, the thread distribution policy and the layering result of the user representation may cooperate with each other, that is, when a thread is issued, first thread data and/or event data are issued to a consuming service line with a high thread matching degree according to a thread matching relationship between the user representation and the consuming service line, and then a competing relationship of the consuming service lines, a priority of the consuming service line, and a distribution quantity in the thread distribution policy are considered, so that thread data and/or event data with a high thread matching degree, a non-conflicting competing relationship, and a proper quantity are distributed to different consuming service lines. In addition, the delivered thread data and/or event data can be selected and matched in a targeted manner according to different consumption service lines, for example, for the consumption service line a, the delivered thread data may be "user B, gender, woman, age 30, accumulated 500 yuan consumed on the consumption service line a in nearly 7 days, and the hierarchical level for the consumption service line a is high". By the distribution mode, each clue data and/or event data can be distributed to a proper consumption service line, so that the total value of the optimal life cycle of the clue data (Best LTV, best life time value) is improved
206. And acquiring a clue inquiry request, and inquiring the user portrait corresponding to the clue unique identifier according to the clue unique identifier carried in the clue inquiry request.
207. And acquiring a cable circling request, and inquiring at least one user portrait corresponding to at least one clue tag value according to at least one clue tag value carried in the cable circling request.
Specifically, the computer device may receive an inquiry request sent by a user, and search, according to the inquiry request, information such as a corresponding user portrait and a clue tag value corresponding to the user portrait in the database. The query request may be a click request or a circle selection request. The query request refers to a query request carrying a clue unique identifier (such as a user identifier or a user mobile phone number) and a user portrait (such as a user portrait corresponding to the user identifier) corresponding to the clue unique identifier can be queried according to the clue query request; the circled request refers to a query request carrying at least one cue tag value (e.g., age 30, gender girl), and at least one user representation (e.g., a user group with age 30, gender girl) corresponding to the cue tag value can be queried according to the cue circled request. By the method, the user of each service line can inquire the required user portrait, so that the cable data and/or the event data can be screened in a targeted manner, and the flexibility of issuing the cable data is further improved.
According to the processing method of the clue data, clue data and/or label data on a plurality of service supply lines are collected, clue values corresponding to the user portraits are inquired, and the information is stored in the user portraits in the form of the clue label values so as to conduct layering of the user portraits and distribution of clues, so that clue distribution can be suitable for a multi-service line distribution scene, and accuracy of clue data distribution is effectively improved. In addition, the method provides a click-check interface and a circle-selection interface of the user portrait, so that the user can conveniently inquire the corresponding user portrait through the click-check interface and the circle-selection interface at any time and actively screen clue data, and the flexibility of clue distribution is enhanced.
Further, as a refinement and an extension of the specific implementation of the foregoing embodiment, in order to fully illustrate the implementation process of the present embodiment, the present embodiment provides a processing method of thread data in combination with a specific application scenario, taking as an example that the method is applied to a thread middlebox as shown in fig. 3 to 6, the method includes the following steps: first, the interface layer of the cue middle station can uniformly collect cue data and/or event data supplied to each service line (upstream channel layer) in a service party, wherein the cue data and the event data can be collected by unifying the cue incoming line and the embedded data stream (Flink), or can be collected by actively pulling the service data and processing the service data into the cue data/event data. Then, the business service layer of the cue middle station can preprocess the acquired cue data and/or event data to obtain a cue tag value corresponding to the cue data and/or event data, wherein the cue tag value can be set by a cue tag template, and the cue tag in the cue tag template can be data related to purchasing ability or data related to purchasing intention, and after obtaining the cue tag value, the cue tag value can be stored in a corresponding user portrait, wherein the user portrait can be respectively stored in different types of databases and can be synchronized with data, and click query requests of the user portrait and selection query requests of user crowds can be received through different data query interfaces. Then, the business service layer of the thread middle station can inquire the thread value corresponding to the user image through the thread sandbox according to the thread tag value, and store the thread value corresponding to the user image in the corresponding user image in the form of the thread tag value. Next, the business service layer of the thread middle station can perform layering processing on the user portrait according to each thread label value in the user portrait through a pre-trained layering calculation rule and a layering algorithm model to obtain a layering result of the user portrait, namely a thread matching relation between the user portrait and each consumption business line, and finally, the business service layer of the business middle station can sequentially distribute thread data/or event data corresponding to the user portrait to each consumption business line through an interface layer of the thread middle station according to a preset thread distribution strategy and a layering result of the user portrait. The method can finely layer the user portrait and reasonably distribute the cue data, so that the cue distribution can be suitable for a multi-service line distribution scene, and the accuracy of the cue data distribution is effectively improved. In addition, the method can effectively avoid the problem of repeated development of a plurality of service lines by providing a unified collection, management and distribution mode of the clue data, thereby improving the processing efficiency of the clue data and reducing the development and maintenance cost of the clue data processing system.
Further, as a specific implementation of the method shown in fig. 1 to fig. 6, the present embodiment provides a processing apparatus for cable data, as shown in fig. 7, the apparatus includes: a thread collection module 31, a thread preprocessing module 32, a thread layering module 33 and a thread distribution module 34, wherein:
a thread collecting module 31, configured to collect thread data and/or event data provided to each service line;
a clue preprocessing module 32, configured to preprocess the clue data and/or the event data to obtain a clue tag value corresponding to the clue data and/or the event data, and store the clue tag value in the corresponding user representation;
the clue layering module 33 is used for layering the user portrait according to the clue label value through a pre-trained layering algorithm model to obtain a layering result of the user portrait;
and the clue distribution module 34 is used for distributing clue data/event data corresponding to the user representation to the corresponding consumption service line according to a preset clue distribution strategy and the layering result of the user representation.
In a specific application scenario, the thread acquisition module 31 may be specifically configured to respectively acquire to-be-stored thread data and buried point data of each service line by using a thread acquisition tool and a data stream acquisition tool, so as to obtain thread data and/or event data of each service line; and/or pulling the service data of each service supply line, and processing the service data to obtain clue data and/or event data of each service supply line.
In a specific application scenario, the cue preprocessing module 32 is specifically configured to compare cue data and/or event data with a preset cue tag value template, and screen out a cue tag and a cue tag value corresponding to the cue data and/or event data; according to the identification information carried in the clue data and/or the event data, finding the user portrait corresponding to the clue data and/or the event data; and storing the clue tag value corresponding to the clue data and/or the event data in the user portrait corresponding to the clue data and/or the event data.
In a specific application scenario, the cue layering module 33 is specifically configured to sequentially input each cue label value corresponding to the user portrait into a pre-trained layering algorithm model to obtain a layering result of the user portrait; and storing the layering result of the user portrait in the form of a clue tag value, wherein the layering result of the user portrait comprises a consumption service line corresponding to the user portrait and a clue matching degree between the user portrait and the consumption service line.
In a specific application scenario, as shown in fig. 7, the apparatus further includes a thread query module 35, where the thread query module 35 is specifically configured to obtain a query request of a user representation, where the query request of the user representation carries at least one thread tag value; querying at least one user representation and a corresponding cue value of the at least one user representation according to the at least one cue tag value; a cue value corresponding to each of the at least one user representation is stored in the corresponding user representation in the form of a cue tag value.
In a specific application scenario, the thread distribution strategy comprises one or more of a thread issuing mode, a thread competition rule, a thread recovery identifier, a distribution priority of each consumption service line and a distribution number of each consumption service line; a thread distribution module 34, specifically configured to determine, according to the layering result of the user representation, a consumption service line corresponding to the user representation and a thread matching degree between the user representation and each consumption service line; and distributing the thread data/event data corresponding to the user image to the consumption service line corresponding to the user image in a message mode according to the thread distribution strategy and the thread matching degree between the user image and each consumption service line.
In a specific application scenario, the thread query module 35 may be further configured to obtain a thread point query request and/or a thread circling request, where the thread point query request carries a thread unique identifier, and the thread circling request carries at least one thread tag value; and querying the user portrait corresponding to the thread unique identifier according to the thread unique identifier, and/or querying at least one user portrait corresponding to at least one thread tag value according to at least one thread tag value.
It should be noted that other corresponding descriptions of the functional units related to the apparatus for processing cable data provided in this embodiment may refer to the corresponding descriptions in fig. 1 to fig. 6, and are not described herein again.
Further, as a specific implementation of the method shown in fig. 1 to fig. 6, this embodiment provides a cable middle station, as shown in fig. 8, where the cable middle station includes an interface layer 41 and a service processing layer 42, where:
the interface layer 41 is used for collecting clue data and/or event data of each service line;
the service processing layer 42 is used for preprocessing the clue data and/or the event data to obtain a clue tag value corresponding to the clue data and/or the event data, and storing the clue tag value in a corresponding user portrait;
the business processing layer 42 is further configured to perform layering processing on the user portrait according to the clue tag value through a pre-trained layering algorithm model to obtain a layering result of the user portrait;
the interface layer 41 is further configured to distribute, according to a preset clue distribution policy, clue data and/or event data corresponding to the user representation to a corresponding consumption service line according to a layering result of the user representation.
In a specific application scenario, the interface layer 41 may be specifically configured to respectively acquire cue data to be stored in a storage and buried point data of each service line by using a cue acquisition tool and a data stream acquisition tool, so as to obtain cue data and/or event data of each service line; and/or pulling the service data of each service supply line, and processing the service data to obtain clue data and/or event data of each service supply line.
In a specific application scenario, the service processing layer 42 is specifically configured to compare the cue data and/or the event data with a preset cue tag value template, and screen out a cue tag and a cue tag value corresponding to the cue data and/or the event data; according to the identification information carried in the clue data and/or the event data, finding the user portrait corresponding to the clue data and/or the event data; and storing the clue tag value corresponding to the clue data and/or the event data in the user portrait corresponding to the clue data and/or the event data.
In a specific application scenario, the service processing layer 42 may be further configured to sequentially input each clue label value corresponding to the user portrait into a pre-trained hierarchical algorithm model to obtain a hierarchical result of the user portrait; and storing the layering result of the user portrait in the form of a clue tag value, wherein the layering result of the user portrait comprises a consumption service line corresponding to the user portrait and a clue matching degree between the user portrait and the consumption service line.
In a specific application scenario, the service processing layer 42 may be further configured to obtain a query request of the user representation, where the query request of the user representation carries at least one clue tag value; querying at least one user representation and a corresponding cue value of the at least one user representation according to the at least one cue tag value; a cue value corresponding to each of the at least one user representation is stored in the corresponding user representation in the form of a cue tag value.
In a specific application scenario, the thread distribution strategy comprises one or more of a thread issuing mode, a thread competition rule, a thread recovery identifier, a distribution priority of each consumption service line and a distribution number of each consumption service line; the interface layer 41 is specifically used for determining a consumption service line corresponding to the user portrait and a clue matching degree between the user portrait and each consumption service line according to a layering result of the user portrait; and distributing the thread data/event data corresponding to the user image to the consumption service line corresponding to the user image in a message mode according to the thread distribution strategy and the thread matching degree between the user image and each consumption service line.
In a specific application scenario, the service processing layer 42 may be further configured to obtain a clue point query request and/or a clue selection request, where the clue point query request carries a clue unique identifier, and the clue selection request carries at least one clue tag value; and querying the user portrait corresponding to the thread unique identifier according to the thread unique identifier, and/or querying at least one user portrait corresponding to at least one thread tag value according to at least one thread tag value.
It should be noted that other corresponding descriptions of the functional units related to the cable center station provided in this embodiment may refer to the corresponding descriptions in fig. 1 to fig. 6, and are not described herein again.
Based on the methods shown in fig. 1 to 6, correspondingly, the present embodiment further provides a storage medium, on which a computer program is stored, and the computer program, when executed by a processor, implements the method for processing the clue data shown in fig. 1 to 6.
Based on such understanding, the technical solution of the present application may be embodied in the form of a software product, and the software product to be identified may be stored in a non-volatile storage medium (which may be a CD-ROM, a usb disk, a removable hard disk, or the like), and include several instructions for enabling a computer device (which may be a personal computer, a server, or a network device) to execute the method according to the implementation scenarios of the present application.
Based on the method shown in fig. 1 to fig. 6 and the embodiments of the processing apparatus of thread data shown in fig. 3 and fig. 4, in order to achieve the above object, the present embodiment further provides an entity device for processing thread data, which may be specifically a personal computer, a server, a smart phone, a tablet computer, a smart watch, or other network devices, and the entity device includes a storage medium and a processor; a storage medium for storing a computer program; a processor for executing a computer program for implementing the above-described method as shown in fig. 1 to 6.
Optionally, the entity device may further include a user interface, a network interface, a camera, a Radio Frequency (RF) circuit, a sensor, an audio circuit, a WI-FI module, and the like. The user interface may include a Display screen (Display), an input unit such as a keypad (Keyboard), etc., and the optional user interface may also include a USB interface, a card reader interface, etc. The network interface may optionally include a standard wired interface, a wireless interface (e.g., WI-FI interface), etc.
Those skilled in the art will appreciate that the physical device structure of a processing of the data of the cable provided in the present embodiment does not constitute a limitation to the physical device, and may include more or less components, or combine some components, or arrange different components.
The storage medium may further include an operating system and a network communication module. The operating system is a program for managing the hardware of the above-mentioned entity device and the software resources to be identified, and supports the operation of the information processing program and other software and/or programs to be identified. The network communication module is used for realizing communication among components in the storage medium and communication with other hardware and software in the information processing entity device.
Through the above description of the embodiments, those skilled in the art will clearly understand that the present application can be implemented by software plus a necessary general hardware platform, and can also be implemented by hardware. By applying the technical scheme of the application, clue data and/or event data supplied to a service line are collected firstly, then the collected clue data and/or event data are preprocessed to obtain clue label values corresponding to the clue data and/or event data, the clue label values are stored in corresponding user portraits, then the user portraits are layered through a pre-trained layered algorithm model according to the clue label values to obtain layered results of the user portraits, and finally the clue data and/or event data corresponding to the user portraits are distributed to corresponding consumption service lines according to a preset clue distribution strategy and layered results of the user portraits. Compared with the prior art, the method can enrich clue information by collecting clue data and/or event data supplied to a plurality of service lines, and can construct and enrich user portrait information by performing labeling processing on the clue data and/or event data, so that the user portrait can be finely layered and reasonably distributed, clue distribution can be suitable for a multi-service line distribution scene, and the optimal life cycle total value of the clue data is effectively improved. In addition, the method effectively avoids the problem of repeated development of a plurality of service lines by providing a unified collection, management and distribution mode of the clue data, improves the processing efficiency of the clue data and reduces the development and maintenance cost of the clue data processing system.
Those skilled in the art will appreciate that the figures are merely schematic representations of one preferred implementation scenario and that the blocks or flow diagrams in the figures are not necessarily required to practice the present application. Those skilled in the art will appreciate that the modules in the devices in the implementation scenario may be distributed in the devices in the implementation scenario according to the description of the implementation scenario, or may be located in one or more devices different from the present implementation scenario with corresponding changes. The modules of the implementation scenario may be combined into one module, or may be further split into a plurality of sub-modules.
The above application serial numbers are for description purposes only and do not represent the superiority or inferiority of the implementation scenarios. The above disclosure is only a few specific implementation scenarios of the present application, but the present application is not limited thereto, and any variations that can be made by those skilled in the art are intended to fall within the scope of the present application.
Claims (11)
1. A method for processing data of a cable, the method comprising:
collecting clue data and/or event data of each service line;
preprocessing the clue data and/or the event data to obtain a clue tag value corresponding to the clue data and/or the event data, and storing the clue tag value in a corresponding user portrait;
carrying out layering processing on the user portrait according to the clue label value through a pre-trained layering algorithm model to obtain a layering result of the user portrait;
and according to a preset clue distribution strategy, distributing clue data/or event data corresponding to the user image to a corresponding consumption service line according to the layering result of the user image.
2. The method of claim 1, wherein collecting the thread data and/or event data for each service line comprises:
respectively acquiring lead data to be stored and buried point data of each service line by using a lead acquisition tool and a data stream acquisition tool to obtain lead data and/or event data of each service line;
and/or pulling the service data of each service supply line, and processing the service data to obtain clue data and/or event data of each service supply line.
3. The method of claim 1, wherein preprocessing the cue data and/or event data to obtain cue tag values corresponding to the cue data and/or event data and storing the cue tag values in a corresponding user representation comprises:
comparing the clue data and/or the event data with a preset clue label value template, and screening out clue labels and clue label values corresponding to the clue data and/or the event data;
according to the identification information carried in the clue data and/or the event data, finding the user portrait corresponding to the clue data and/or the event data;
and storing the clue tag value corresponding to the clue data and/or the event data in the user portrait corresponding to the clue data and/or the event data.
4. The method of claim 1, wherein the pre-trained layering algorithm model performs layering on the user representation according to the cue label values to obtain a layering result of the user representation, and the method comprises:
sequentially inputting each clue label value corresponding to the user portrait into the pre-trained layering algorithm model to obtain a layering result of the user portrait;
and storing the layering result of the user representation in the form of a clue tag value, wherein the layering result of the user representation comprises a consumption service line corresponding to the user representation and a clue matching degree with the consumption service line.
5. The method of claim 1 or 4, wherein before the user representation is layered according to the cue label values through a pre-trained layered algorithm model to obtain a layered result of the user representation, the method further comprises:
acquiring a query request of a user portrait, wherein the query request of the user portrait carries at least one clue tag value;
querying at least one user representation and a respective corresponding cue value of the at least one user representation according to the at least one cue tag value;
and storing the clue value corresponding to each user portrait in the corresponding user portrait in the form of a clue tag value.
6. The method of claim 1, wherein the thread distribution policy includes one or more of a thread issuing manner, a consumption service line competition rule, a thread recycling identifier, a distribution priority of each consumption service line, and a distribution number of each consumption service line;
the distributing the thread data/event data corresponding to the user portrait to the corresponding consumption service line according to the preset thread distribution strategy and the layering result of the user portrait comprises:
determining a consumption service line corresponding to the user portrait and a clue matching degree between the user portrait and each consumption service line according to the layering result of the user portrait;
and distributing the thread data/event data corresponding to the user image to the consumption service line corresponding to the user image in a message mode according to the thread distribution strategy and the thread matching degree between the user image and each consumption service line.
7. The method of claim 1, further comprising:
obtaining a clue point search request and/or a clue selection request, wherein a clue unique identifier carried in the clue point search request carries at least one clue tag value;
and inquiring the user portrait corresponding to the thread unique identifier according to the thread unique identifier, and/or inquiring at least one user portrait corresponding to the at least one thread tag value according to the at least one thread tag value.
8. An apparatus for processing data of a cable, the apparatus comprising:
the clue acquisition module is used for acquiring clue data and/or event data supplied to each service line;
a clue preprocessing module, configured to preprocess the clue data and/or event data to obtain a clue tag value corresponding to the clue data and/or event data, and store the clue tag value in a corresponding user representation;
the clue layering module is used for carrying out layering processing on the user portrait according to the clue label value through a pre-trained layering algorithm model to obtain a layering result of the user portrait;
and the clue distribution module is used for distributing clue data/event data corresponding to the user portrait to a corresponding consumption service line according to a preset clue distribution strategy and the layering result of the user portrait.
9. A cable-in-line station, comprising an interface layer and a service processing layer, wherein,
the interface layer is used for acquiring clue data and/or event data of each service line;
the business processing layer is used for preprocessing the clue data and/or the event data to obtain a clue tag value corresponding to the clue data and/or the event data and storing the clue tag value in a corresponding user portrait;
the business processing layer is also used for carrying out layering processing on the user portrait according to the clue label value through a pre-trained layering algorithm model to obtain a layering result of the user portrait;
and the interface layer is also used for distributing the clue data/or the event data corresponding to the user portrait to the corresponding consumption service line according to a preset clue distribution strategy and the layering result of the user portrait.
10. A storage medium having a computer program stored thereon, the computer program, when being executed by a processor, realizing the steps of the method of any one of claims 1 to 7.
11. A computer arrangement comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the computer program realizes the steps of the method of any one of claims 1 to 7 when executed by the processor.
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