CN112801763A - Touch and reach scheme generation method and device and electronic equipment - Google Patents
Touch and reach scheme generation method and device and electronic equipment Download PDFInfo
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Abstract
The embodiment of the application provides a method and a device for generating a reach scheme and electronic equipment, wherein the method comprises the following steps: obtaining information to be sent which is to be sent to a target entity object and needs to be processed by the target entity object, wherein the target entity object is an entity object for providing service for a user; obtaining a target subject type to which the target entity object belongs; acquiring a target reach parameter corresponding to the target theme type according to the target theme type and a reach parameter prediction model, wherein the reach parameter prediction model is a model for predicting the reach parameter corresponding to the theme type according to the theme type; and generating a target touch scheme for guiding the information to be sent to the target entity object according to the target touch parameter. The method can improve the touch efficiency of sending the message to be sent to the target entity object, and can improve the response efficiency and the processing efficiency of the target entity object to the obtained message to be sent.
Description
Technical Field
The application relates to the field of computers, in particular to a method and a device for generating a reach scheme and electronic equipment.
Background
With the popularization of the internet, the consumption of users on the internet platform in daily life becomes more and more popular. Such as online shopping, online ordering, etc.
In the prior art, a user puts forward service request information for a current order in various consuming processes of an online service platform, and the online service platform generates the service request information of the user into a reach scheme which is sent to a target entity object. However, the response rate and the processing rate of the target entity object to the received reach scheme are both low, so that the service request information of the user cannot be fed back and processed in time, and the consumption experience of the user is affected.
Therefore, how to determine a reach scheme for sending information to a target entity object, wherein the information includes information to be processed by the target entity object, is a problem to be solved.
Disclosure of Invention
The embodiment of the application provides a reach scheme generation method, which is used for determining a reach scheme used for sending information to be processed of a target entity object, wherein the information comprises information required to be processed by the target entity object. The embodiment of the application also provides a touch scheme generation device and electronic equipment.
The embodiment of the application provides a method for generating a reach scheme, which comprises the following steps: obtaining information to be sent which is to be sent to a target entity object and needs to be processed by the target entity object, wherein the target entity object is an entity object for providing service for a user; obtaining a target subject type to which the target entity object belongs; acquiring a target reach parameter corresponding to the target theme type according to the target theme type and a reach parameter prediction model, wherein the reach parameter prediction model is a model for predicting the reach parameter corresponding to the theme type according to the theme type; and generating a target touch scheme for guiding the information to be sent to the target entity object according to the target touch parameter.
Optionally, the obtaining of the target topic type to which the target entity object belongs includes: and inputting the identification information of the target entity object into a theme type prediction model for predicting the theme type to which the entity object belongs according to the identification information of the entity object to obtain the target theme type to which the target entity object belongs.
Optionally, the topic type prediction model is obtained as follows: acquiring basic data of a historical entity object and historical processing data of information which is processed by the historical entity object and sent to the historical entity object; obtaining historical characteristic data of the historical entity object according to the basic data of the historical entity object and the historical processing data of the historical entity object; constructing a relation matrix between the identification information of the historical entity object and the historical characteristic data; obtaining a relation matrix between the identification information of the historical entity object and the specified theme type according to the relation matrix between the identification information of the historical entity object and the historical characteristic data and the specified theme type; and obtaining the theme type prediction model according to the relation matrix between the identification information of the historical entity object and the specified theme type.
Optionally, the basic data of the historical entity object includes at least one of the following data: type data of the historical entity object; tag data of the historical entity object; category data to which the historical entity object belongs; service time data of the historical entity object; service mode data of the historical entity object.
Optionally, the history processing data of the history entity object includes at least one of the following data: the number of the information touched by the historical entity object in a preset time range; reach time data of the reached information of the historical entity object; the historical entity object responds to response time data of the touched information; processing duration data of the touched information is processed by the historical entity object; and the historical entity object processes the processing mode data of the touched information.
Optionally, the obtaining the relationship matrix between the identification information of the historical entity object and the specified topic type according to the relationship matrix between the identification information of the historical entity object and the historical feature data and the specified topic type includes: obtaining a relation matrix between the identification information of the historical entity object and the appointed initial theme type according to the relation matrix between the identification information of the historical entity object and the historical characteristic data and the appointed initial theme type; if the relation matrix between the identification information of the historical entity object and the specified initial theme type does not meet the preset condition, adjusting the initial theme type to obtain the adjusted theme type; obtaining a relation matrix between the identification information of the historical entity object and the adjusted subject type according to the relation matrix between the identification information of the historical entity object and the historical characteristic data and the adjusted initial subject type; the obtaining the topic type prediction model according to the relationship matrix between the identification information of the historical entity object and the specified topic type includes: and obtaining the theme type prediction model according to the relation matrix between the identification information of the historical entity object and the adjusted theme type.
Optionally, the target topic type is one of the following topic types: a service scale type of the target entity object; a service feature type of the target entity object; the response time type of the information that the response of the target entity object is touched; and the target entity object processes the processing mode type of the touched information.
Optionally, the reach parameter prediction model is obtained as follows: obtaining a history subject type to which a history entity object belongs; obtaining historical processing aging data of the processed information of the historical entity object in different historical time types; constructing a relation matrix among the historical theme type, the historical time type and the historical processing aging data; and according to the relation matrix among the historical theme type, the historical time type and the historical processing aging data, obtaining the reach parameter prediction model for predicting the time type with the highest processing aging corresponding to the theme type according to the theme type.
Optionally, the obtaining, according to the target topic type and the reach parameter prediction model, a target reach parameter corresponding to the target topic type includes: acquiring a target time type with the highest processing timeliness corresponding to the target theme type according to the target theme type and the touch parameter prediction model; the target reaching scheme comprises guiding information used for guiding the information to be sent to the target entity object at the target time corresponding to the target time type with the highest processing timeliness corresponding to the target theme type.
Optionally, the target access scheme further includes at least one of the following information: frequency information for guiding the information to be sent to the target entity object; and sending mode information used for guiding the information to be sent to the target entity object.
Optionally, the method further includes: and sending the information to be sent to the target entity object according to the target touch scheme.
Optionally, the information to be sent includes at least one of the following information: the user complains the information of the target entity object; query information of the user aiming at the target entity object; (ii) a receipt refund information for the target entity object; the information of the user for canceling the order of the target entity object; negative comment information of the user for the target entity object.
The present application further provides a reach scheme generating apparatus, including: a to-be-sent message obtaining unit, configured to obtain to-be-sent information to be sent to a target entity object and to be processed by the target entity object, where the target entity object is an entity object that provides a service for a user. And the target subject type obtaining unit is used for obtaining the target subject type to which the target entity object belongs. And the target reach parameter obtaining unit is used for obtaining a target reach parameter corresponding to the target theme type according to the target theme type and a reach parameter prediction model, and the reach parameter prediction model is a model used for predicting the reach parameter corresponding to the theme type according to the theme type. And the target touch scheme generating unit is used for generating a target touch scheme for guiding the information to be sent to the target entity object according to the target touch parameters.
Optionally, the target topic type obtaining unit is specifically configured to input the identification information of the target entity object into a topic type prediction model for predicting a topic type to which the entity object belongs according to the identification information of the entity object, so as to obtain the target topic type to which the target entity object belongs.
Optionally, the topic type prediction model is obtained as follows: acquiring basic data of a historical entity object and historical processing data of information which is processed by the historical entity object and sent to the historical entity object; obtaining historical characteristic data of the historical entity object according to the basic data of the historical entity object and the historical processing data of the historical entity object; constructing a relation matrix between the identification information of the historical entity object and the historical characteristic data; obtaining a relation matrix between the identification information of the historical entity object and the specified theme type according to the relation matrix between the identification information of the historical entity object and the historical characteristic data and the specified theme type; and obtaining the theme type prediction model according to the relation matrix between the identification information of the historical entity object and the specified theme type.
Optionally, the basic data of the historical entity object includes at least one of the following data: type data of the historical entity object; tag data of the historical entity object; category data to which the historical entity object belongs; service time data of the historical entity object; service mode data of the historical entity object.
Optionally, the history processing data of the history entity object includes at least one of the following data: the number of the information touched by the historical entity object in a preset time range; reach time data of the reached information of the historical entity object; the historical entity object responds to the response time data of the touched information, and the historical entity object processes the processing time length data of the touched information; and the historical entity object processes the processing mode data of the touched information.
Optionally, the obtaining the relationship matrix between the identification information of the historical entity object and the specified topic type according to the relationship matrix between the identification information of the historical entity object and the historical feature data and the specified topic type includes: obtaining a relation matrix between the identification information of the historical entity object and the appointed initial theme type according to the relation matrix between the identification information of the historical entity object and the historical characteristic data and the appointed initial theme type; if the relation matrix between the identification information of the historical entity object and the specified initial theme type does not meet the preset condition, adjusting the initial theme type to obtain the adjusted theme type; obtaining a relation matrix between the identification information of the historical entity object and the adjusted subject type according to the relation matrix between the identification information of the historical entity object and the historical characteristic data and the adjusted initial subject type; the obtaining the topic type prediction model according to the relationship matrix between the identification information of the historical entity object and the specified topic type includes: and obtaining the theme type prediction model according to the relation matrix between the identification information of the historical entity object and the adjusted theme type.
Optionally, the target topic type is one of the following topic types: a service scale type of the target entity object; a service feature type of the target entity object; the response time type of the information that the response of the target entity object is touched; and the target entity object processes the processing mode type of the touched information.
Optionally, the reach parameter prediction model is obtained as follows: obtaining a history subject type to which a history entity object belongs; obtaining historical processing aging data of the processed information of the historical entity object in different historical time types; constructing a relation matrix among the historical theme type, the historical time type and the historical processing aging data; and according to the relation matrix among the historical theme type, the historical time type and the historical processing aging data, obtaining the reach parameter prediction model for predicting the time type with the highest processing aging corresponding to the theme type according to the theme type.
Optionally, the target reach parameter obtaining unit is specifically configured to obtain, according to the target topic type and the reach parameter prediction model, a target time type with the highest processing timeliness corresponding to the target topic type; the target reaching scheme comprises guiding information used for guiding the information to be sent to the target entity object at the target time corresponding to the target time type with the highest processing timeliness corresponding to the target theme type.
Optionally, the target access scheme further includes at least one of the following information: frequency information for guiding the information to be sent to the target entity object; and sending mode information used for guiding the information to be sent to the target entity object.
Optionally, the apparatus further comprises: and the sending unit is used for sending the information to be sent to the target entity object according to the target touch scheme.
Optionally, the information to be sent includes at least one of the following information: the user complains the information of the target entity object; query information of the user aiming at the target entity object; (ii) a receipt refund information for the target entity object; the information of the user for canceling the order of the target entity object; negative comment information of the user for the target entity object.
The present application further provides an electronic device, comprising: a processor; and a memory for storing a computer program which, when the apparatus is powered on and the computer program is run by the processor, performs the method described above.
The present application also provides a storage medium, wherein the storage medium stores a computer program, and the computer program is executed by a processor to execute the method.
Compared with the prior art, the method has the following advantages:
the embodiment of the application provides a method for generating a touch scheme, which includes obtaining information to be sent, which is to be sent to a target entity object and needs to be processed by the target entity object, wherein the target entity object is an entity object for providing service for a user; obtaining a target subject type to which the target entity object belongs; acquiring a target reach parameter corresponding to the target theme type according to the target theme type and a reach parameter prediction model, wherein the reach parameter prediction model is a model for predicting the reach parameter corresponding to the theme type according to the theme type; and generating a target touch scheme for guiding the information to be sent to the target entity object according to the target touch parameter.
In the method, the target entity object is classified according to the target subject type to which the target entity object belongs, the target touch parameter corresponding to the target subject type is obtained, and the information to be sent is sent to the target entity object according to the target touch parameter. The target touch scheme is generated according to the target touch parameter corresponding to the target subject type to which the target entity object belongs, so that the to-be-sent message is sent to the target entity object according to the target touch scheme, the touch efficiency of sending the to-be-sent message to the target entity object can be improved, and the response efficiency and the processing efficiency of the target entity object to the acquired to-be-sent message can be improved.
Drawings
Fig. 1 is a specific scenario embodiment of a reach scheme generation method provided in the embodiment of the present application.
Fig. 2 is a method for obtaining a topic type prediction model provided in the embodiment of the present application.
Fig. 3 is a method for obtaining a reach parameter prediction model according to an embodiment of the present disclosure.
Fig. 4 is a flowchart of a reach plan generating method provided in the first embodiment of the present application.
Fig. 5 is a flowchart of a reach plan generating apparatus provided in a second embodiment of the present application.
Fig. 6 is a schematic diagram of an electronic device provided in a ninth embodiment of the present application.
Detailed Description
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present application. This application is capable of implementation in many different ways than those herein set forth and of similar import by those skilled in the art without departing from the spirit of this application and is therefore not limited to the specific implementations disclosed below.
In order to more clearly show the reach scheme generation method provided by the embodiment of the present application, an application scenario of the reach scheme generation method provided by the embodiment of the present application is first introduced. In practical application, when receiving information to be sent which needs to be processed by a target entity object, a terminal service platform generates a reach scheme for sending the information to be sent to the target entity object according to the information to be sent. However, the touch scheme in the prior art is not only low in touch efficiency, but also low in response rate and processing rate after the target entity object receives the touch scheme; and a large amount of invalid reach messages are sent, so that the experience effect of the user or the target entity object is reduced. Therefore, the embodiment of the application provides a reach scheme generation method capable of efficiently delivering the target entity object and efficiently processing the target entity object.
The embodiment takes the user complaint message as an example to describe the obtaining process of the above-mentioned reaching scheme. The following description is made with reference to fig. 1 to 3.
Please refer to fig. 1, which is a specific scenario embodiment of a reach scheme generation method provided in an embodiment of the present application. First, information to be sent, which is to be sent to a target entity object and needs to be processed by the target entity object, is obtained, and the target entity object is an entity object providing a service for a user. As shown in fig. 1, after a user a purchases an order from a store of a merchant B on line in an APP, a complaint message is proposed for the order and is ready to be sent to the complaint message of the merchant B. Secondly, the server side obtains the identification information of the merchant B according to the complaint message, obtains the target subject type of the merchant B, and specifically inputs the identification information of the merchant B into a subject type prediction model to obtain the target subject type of the merchant B. And thirdly, after the target theme type of the merchant B is obtained, obtaining a target reach parameter corresponding to the target theme type of the merchant B according to the target theme type and the reach parameter prediction model. Fourthly, generating a target reach scheme of the merchant B according to the target subject type and the target reach parameters of the merchant B, and the reach type and the basic reach scheme, wherein the target reach scheme is used for guiding the complaint information to be sent to the merchant B according to the target reach parameters.
The target theme type corresponding to the identification information of the merchant B is obtained according to the identification information of the merchant B, the identification information of the merchant B is input into the theme type prediction model, and the target theme type corresponding to the identification information output by the theme type prediction model is obtained. Please refer to fig. 2, which is a method for obtaining a topic type prediction model provided in the embodiment of the present application, and the specific method is as follows: firstly, acquiring historical characteristic data of a historical merchant according to basic data of the historical merchant and historical processing data of the historical merchant; and establishing a relation matrix between the identification information of the historical merchant and the characteristic data. Secondly, an initial theme type is appointed to the historical merchant, and a relation matrix between the identification information of the historical merchant and the appointed initial theme type is determined according to the relation matrix and the initial theme type appointed by the historical merchant. And if the relation matrix between the identification information of the historical merchant and the specified initial theme type does not meet the preset condition, adjusting the initial theme type until the relation matrix between the adjusted theme type and the identification information of the historical merchant meets the preset condition. And finally, obtaining the theme type prediction model according to the relationship matrix between the identification information of the historical entity object and the adjusted theme type.
In addition, according to the target theme type and the reach parameter prediction model, the target reach parameter corresponding to the target theme type of the merchant B is obtained, specifically, the target theme type is input into the reach parameter prediction model, and the target reach parameter corresponding to the target theme type of the merchant B output by the reach parameter prediction model is obtained. Specifically, the time type with the highest processing timeliness corresponding to the theme type is predicted according to the theme type. Please refer to fig. 3, which is a method for obtaining a reach parameter prediction model according to an embodiment of the present application, specifically as follows: obtaining a history subject type to which a history entity object belongs; obtaining historical processing aging data of the processed information of the historical entity object in different historical time types; constructing a relation matrix among the historical theme type, the historical time type and the historical processing aging data; and according to the relation matrix among the historical theme type, the historical time type and the historical processing aging data, obtaining the reach parameter prediction model for predicting the time type with the highest processing aging corresponding to the theme type according to the theme type.
After the target subject type of the merchant B and the time type with the highest processing timeliness corresponding to the target subject type are obtained, frequency information and sending mode information for sending the complaint information to the merchant B are obtained. And generating a target reach scheme by combining the basic reach scheme and the reach type according to the target theme type, the target reach parameter, the target reach frequency and the target sending mode information.
The reach type information refers to a reach mode for contacting a reach scheme to a merchant, for example, a short message type, a voice call-out type, a manual call-out type, an APP message push type, a printer receipt printing mode and the like, and the reach scheme is transmitted to a user and the merchant through at least one reach type.
The basic reach scheme information refers to a preset initialization reach scheme for merchants with various theme types, namely a reach scheme template, and is used for generating target reach scheme information matched with the merchants according to the theme type information, the reach parameter information and the reach type information of the merchants.
It should be noted that, the application does not limit the specific application scenario of the reach scheme generation method provided in this embodiment, and the reach scheme generation method may also be used in other application scenarios, for example: the user applies for a receipt, cancels the receipt and the like. The application of the above-mentioned reach plan generating method to the user complaints is only for facilitating understanding of the present application, and is not used to limit the application of the reach plan generating method provided in the present application.
First embodiment
A method for generating a reach scheme is provided in the first embodiment of the present application, and a specific flow is shown in fig. 4, which is a flow chart of the method for generating a reach scheme provided in the first embodiment of the present application. The method for generating a reach scheme for sending a message to be sent, which needs to be processed by a target entity object, to the target entity object, shown in fig. 4, includes: step S401 to step S404.
In the first embodiment of the present application, an execution subject for executing the reach scheme generating method may be a server, and the server may send interaction information to the terminal of the user and the terminal of the target entity object at the same time. The server receives user service request information from a user client, wherein the user service request information is request information for providing service for a user by a target entity object, and the user service request information is used as information to be sent to the target entity object client. And the server processes the information to be sent to generate a target touch scheme for guiding the information to be sent to a target entity object. In the first embodiment of the present application, the information to be sent may be order complaint information of the user a, the client may be an online shopping platform APP, and the target entity object may be a merchant B of the online shopping platform APP.
As shown in fig. 4, in step S401, information to be transmitted, which is to be transmitted to a target entity object and needs to be processed by the target entity object, is obtained, where the target entity object is an entity object that provides a service to a user.
Step S401 is configured to obtain a to-be-sent message that is provided by a user and needs to be processed by a target entity object, and make a data basis for subsequently generating a target reach scheme according to the to-be-sent message.
The target entity object is an entity object providing a service to a user, for example, a merchant B in an online shopping APP.
The message to be sent refers to a service request message provided by the user A for an order A generated by shopping in the shop of the merchant B. The information to be transmitted comprises at least one of the following information: the user complains the information of the target entity object; query information of the user aiming at the target entity object; (ii) a receipt refund information for the target entity object; the information of the user for canceling the order of the target entity object; negative comment information of the user for the target entity object.
In order to improve the response rate and the processing rate of the target entity object to the received message to be sent after the message to be sent to the target entity object is sent to the target entity object, the first embodiment of the present application performs the following analysis and processing on the received message to be sent and the target entity object to generate a target touch scheme, please refer to steps S402-S404.
As shown in fig. 4, in step S402, a target topic type to which the target entity object belongs is obtained.
In this step S402, the step of acquiring, by the user, the target subject type to which the target entity object belongs includes: and inputting the identification information of the target entity object into a theme type prediction model for predicting the theme type to which the entity object belongs according to the identification information of the entity object to obtain the target theme type to which the target entity object belongs.
The identification information of the target entity object refers to name information or identification information of the target entity object, for example, a shop name and a shop identification of the merchant a.
The target subject type to which the target entity object belongs is obtained by classifying all merchants on the online shopping APP according to the subject type.
The topic type prediction model is obtained according to the following steps 1-5:
step 1: and acquiring basic data of a historical entity object and historical processing data of information which is processed by the historical entity object and sent to the historical entity object.
The basic data of the historical entity object comprises at least one of the following data: 1) the type data of the historical entity object, for example, includes KA (key account), TKA (Top key account), CKA (Central key account), and single store customer. 2) Tag data of the historical entity object. 3) Category data to which the historical entity object belongs, such as, for example, a dining category, a beauty category, a nursery category, a new retail category, and so forth. 4) Service time data of the historical entity object, for example, tuesday to sunday, 9 am to 9 pm. 5) And service mode data of the historical entity object, such as a take-out service mode, a food serving mode and the like.
The history processing data of the information sent to the history entity object by the history entity object is history processing data of processing operation of the history entity object on the information to be touched after the server sends the information to be touched to the history entity object.
Wherein the historical processing data of the historical entity object comprises at least one of the following data:
1) the history entity object is touched to the number of information within a preset time range. For example, merchant B receives complaint information, cancellation order information, return order information, etc. by the amount of the contact information within a preset historical period of time.
2) Reach time data of the reached information of the historical entity object.
3) The historical entity object responds to response time data of the touched information. For example, merchant B, upon receiving the complaint information, responds and prepares time data for processing the information.
4) And the historical entity object processes the processing duration data of the touched information. For example, after receiving a piece of complaint information from merchant B during the historical period, merchant B processes all the time length data of the complaint information.
5) And the historical entity object processes the processing mode data of the touched information.
The method is used for making a data base for acquiring the historical characteristic data of the historical entity object after acquiring the basic data and the historical processing data of the historical entity object.
Step 2: and obtaining historical characteristic data of the historical entity object according to the basic data of the historical entity object and the historical processing data of the historical entity object.
And step 3: and constructing a relation matrix between the identification information of the historical entity object and the historical characteristic data.
The step is used for establishing a corresponding relation between the identification information of the historical entity object and the historical characteristic data and is used for establishing a basis for establishing a relation matrix between the identification information of the historical entity object and the formulated theme type.
And 4, step 4: and obtaining a relation matrix between the identification information of the historical entity object and the specified theme type according to the relation matrix between the identification information of the historical entity object and the historical characteristic data and the specified theme type.
Specifically, the method comprises the following steps: obtaining a relation matrix between the identification information of the historical entity object and the appointed initial theme type according to the relation matrix between the identification information of the historical entity object and the historical characteristic data and the appointed initial theme type; if the relation matrix between the identification information of the historical entity object and the specified initial theme type does not meet the preset condition, adjusting the initial theme type to obtain the adjusted theme type; and obtaining a relation matrix between the identification information of the historical entity object and the adjusted theme type according to the relation matrix between the identification information of the historical entity object and the historical characteristic data and the adjusted initial theme type.
It should be noted here that after the relationship matrix between the identification information of the historical entity object and the historical feature data is acquired, an initial topic type is specified for the historical entity object, and the relationship matrix between the identification information of the historical entity object and the specified initial topic type is acquired. And if the relationship matrix does not meet the preset condition, adjusting the initial theme type until the relationship matrix between the identification information of the historical entity object and the adjusted theme type meets the preset condition. And obtaining a topic type prediction model according to the relationship matrix between the identification information of the historical entity object and the adjusted topic type.
And 5: obtaining the topic type prediction model according to the relationship matrix between the identification information of the historical entity object and the specified topic type, including: and obtaining the theme type prediction model according to the relation matrix between the identification information of the historical entity object and the adjusted theme type.
The steps 1 to 5 describe the method for constructing the topic type prediction model, and firstly, the corresponding relation between the identification information and the characteristic data of the historical entity object is established according to the basic data and the historical processing data of the historical entity object. And then, according to the corresponding relation between the identification information and the characteristic data, and in combination with the specified initial theme type, establishing the corresponding relation between the identification information of the historical entity object and the specified theme type. If the corresponding relation between the identification information of the historical entity object and the appointed initial theme type does not accord with the preset condition, the initial theme type is adjusted until the corresponding relation between the adjusted theme type and the identification information accords with the preset condition. And finally, establishing a theme type prediction model according to the corresponding relation between the identification information of the historical entity object and the adjusted theme type.
And after obtaining the theme type prediction model according to the steps, inputting the identification information of the target entity object into the theme type prediction model to obtain the target theme type output by the theme type prediction model.
Wherein the target topic type is one of the following topic types: 1) a service size type of the target entity object. 2) The service characteristic type of the target entity object, for example, the service characteristic of the target entity object belongs to the catering industry, the new retail industry and the like. 3) The response of the target entity object is triggered to the response time type of the information. 4) And the target entity object processes the processing mode type of the touched information.
As shown in fig. 4, in step S403, a target reach parameter corresponding to the target topic type is obtained according to the target topic type and a reach parameter prediction model, where the reach parameter prediction model is a model for predicting a reach parameter corresponding to the topic type according to the topic type.
In this step S403, the target theme type is input into the reach parameter prediction model, and the target reach parameter output by the reach parameter prediction model and corresponding to the target theme type is obtained.
The obtaining of the target reach parameter corresponding to the target topic type according to the target topic type and the reach parameter prediction model includes: acquiring a target time type with the highest processing timeliness corresponding to the target theme type according to the target theme type and the touch parameter prediction model; the target reaching scheme comprises guiding information used for guiding the information to be sent to the target entity object at the target time corresponding to the target time type with the highest processing timeliness corresponding to the target theme type.
The target reaching parameter is a target time type with the highest processing timeliness of the target subject type so as to improve the processing timeliness of the target entity object for processing the message to be reached.
Specifically, after the target time type with the highest processing timeliness corresponding to the target topic type is obtained, the information to be sent is sent to the target entity object at the target time corresponding to the target time type. Therefore, the target reaching scheme includes guiding information for guiding the information to be sent to the target entity object at the target time.
The reach parameter prediction model is obtained by the following method: obtaining a history subject type to which a history entity object belongs; obtaining historical processing aging data of the processed information of the historical entity object in different historical time types; constructing a relation matrix among the historical theme type, the historical time type and the historical processing aging data; and according to the relation matrix among the historical theme type, the historical time type and the historical processing aging data, obtaining the reach parameter prediction model for predicting the time type with the highest processing aging corresponding to the theme type according to the theme type.
It should be noted here that the time type with the highest processing timeliness corresponding to the topic type of the historical entity object may be obtained by processing the historical processing timeliness data of the touched information according to the historical entity object at different time types, and sorting the historical processing timeliness data according to the historical topic type, the historical time type, and the relationship matrix between the historical processing timeliness data. Therefore, a reach parameter prediction model is established according to a relation matrix among the historical theme type, the historical time type and the historical processing aging data. According to the contact parameter prediction model, the theme type, the processing timeliness and the corresponding relation among the time types of the target entity object can be obtained, so that the time type with the highest processing timeliness corresponding to the theme type of the target entity object is obtained. The historical time types include: weekday-holiday, service time-non-service time, early-middle-late-month, and so on. For example, the theme type of the merchant B is a restaurant type brand chain store, the service time types are Monday to Monday, 9 am to 9 pm, and the historical data shows that the merchant B has the highest processing aging between 11 to 14 and 17 to 21, so the time types corresponding to the merchant B with the highest processing aging are 11 to 14 and 17 to 21.
As shown in fig. 4, in step S404, a target reach scheme for guiding the information to be sent to the target entity object is generated according to the target reach parameter.
The target access scheme further comprises at least one of the following information: frequency information for guiding the information to be sent to the target entity object; and sending mode information used for guiding the information to be sent to the target entity object.
And after the time type, the frequency information and the sending mode information for guiding the information to be sent to the target entity object are obtained, the information to be sent is sent to the target entity object according to the target touch parameter information by combining the target theme type.
The target reach scheme is generated based on the following four dimensions of the target entity object, the target subject type to which the target entity object belongs, the reach type, the basic reach scheme and the target reach parameter. After the target theme type and the target reach parameter of the target entity object are obtained in step S402 and step S403, the target reach scheme of the target entity object is obtained by combining the reach type and the basic reach scheme.
The above is a reach scheme generating method capable of efficiently delivering a target entity object and efficiently processing the target entity object, provided by the first embodiment of the present application.
A first embodiment of the present application provides a method for generating a reach scheme, where information to be sent is obtained, where the information to be sent is to be sent to a target entity object and needs to be processed by the target entity object, and the target entity object is an entity object providing a service for a user; obtaining a target subject type to which the target entity object belongs; acquiring a target reach parameter corresponding to the target theme type according to the target theme type and a reach parameter prediction model, wherein the reach parameter prediction model is a model for predicting the reach parameter corresponding to the theme type according to the theme type; and generating a target touch scheme for guiding the information to be sent to the target entity object according to the target touch parameter. In the method, the target entity object is classified according to the target subject type to which the target entity object belongs, the target touch parameter corresponding to the target subject type is obtained, and the information to be sent is sent to the target entity object according to the target touch parameter. The target touch scheme is generated according to the target touch parameter corresponding to the target subject type to which the target entity object belongs, so that the to-be-sent message is sent to the target entity object according to the target touch scheme, the touch efficiency of sending the to-be-sent message to the target entity object can be improved, and the response efficiency and the processing efficiency of the target entity object to the acquired to-be-sent message can be improved.
Second embodiment
Corresponding to the embodiment corresponding to the application scenario of the reach scheme generation method provided by the present application and the reach scheme generation method provided by the first embodiment, a second embodiment of the present application further provides a reach scheme generation device. Since the embodiment of the apparatus is basically similar to the embodiment corresponding to the application scenario and the first embodiment, the description is relatively simple, and for relevant points, reference may be made to the embodiment corresponding to the application scenario and part of the description of the first embodiment. The device embodiments described below are merely illustrative.
Please refer to fig. 5, which is a schematic diagram of a touch scenario generation apparatus provided in a second embodiment of the present application.
The reach scheme generation apparatus provided in the second embodiment of the present application includes:
a to-be-sent message obtaining unit 501, configured to obtain to-be-sent information to be sent to a target entity object and to be processed by the target entity object, where the target entity object is an entity object providing a service for a user.
A target topic type obtaining unit 502, configured to obtain a target topic type to which the target entity object belongs.
A target reach parameter obtaining unit 503, configured to obtain a target reach parameter corresponding to the target topic type according to the target topic type and a reach parameter prediction model, where the reach parameter prediction model is a model used to predict a reach parameter corresponding to the topic type according to the topic type.
A target reach scheme generating unit 504, configured to generate a target reach scheme for guiding to send the information to be sent to the target entity object according to the target reach parameter.
Optionally, the target topic type obtaining unit 502 is specifically configured to input the identification information of the target entity object into a topic type prediction model for predicting a topic type to which the entity object belongs according to the identification information of the entity object, so as to obtain a target topic type to which the target entity object belongs.
Optionally, the topic type prediction model is obtained as follows: acquiring basic data of a historical entity object and historical processing data of information which is processed by the historical entity object and sent to the historical entity object; obtaining historical characteristic data of the historical entity object according to the basic data of the historical entity object and the historical processing data of the historical entity object; constructing a relation matrix between the identification information of the historical entity object and the historical characteristic data; obtaining a relation matrix between the identification information of the historical entity object and the specified theme type according to the relation matrix between the identification information of the historical entity object and the historical characteristic data and the specified theme type; and obtaining the theme type prediction model according to the relation matrix between the identification information of the historical entity object and the specified theme type.
Optionally, the basic data of the historical entity object includes at least one of the following data: type data of the historical entity object; tag data of the historical entity object; category data to which the historical entity object belongs; service time data of the historical entity object; service mode data of the historical entity object.
Optionally, the history processing data of the history entity object includes at least one of the following data: the number of the information touched by the historical entity object in a preset time range; reach time data of the reached information of the historical entity object; the historical entity object responds to the response time data of the touched information, and the historical entity object processes the processing time length data of the touched information; and the historical entity object processes the processing mode data of the touched information.
Optionally, the obtaining the relationship matrix between the identification information of the historical entity object and the specified topic type according to the relationship matrix between the identification information of the historical entity object and the historical feature data and the specified topic type includes: obtaining a relation matrix between the identification information of the historical entity object and the appointed initial theme type according to the relation matrix between the identification information of the historical entity object and the historical characteristic data and the appointed initial theme type; if the relation matrix between the identification information of the historical entity object and the specified initial theme type does not meet the preset condition, adjusting the initial theme type to obtain the adjusted theme type; obtaining a relation matrix between the identification information of the historical entity object and the adjusted subject type according to the relation matrix between the identification information of the historical entity object and the historical characteristic data and the adjusted initial subject type; the obtaining the topic type prediction model according to the relationship matrix between the identification information of the historical entity object and the specified topic type includes: and obtaining the theme type prediction model according to the relation matrix between the identification information of the historical entity object and the adjusted theme type.
Optionally, the target topic type is one of the following topic types: a service scale type of the target entity object; a service feature type of the target entity object; the response time type of the information that the response of the target entity object is touched; and the target entity object processes the processing mode type of the touched information.
Optionally, the reach parameter prediction model is obtained as follows: obtaining a history subject type to which a history entity object belongs; obtaining historical processing aging data of the processed information of the historical entity object in different historical time types; constructing a relation matrix among the historical theme type, the historical time type and the historical processing aging data; and according to the relation matrix among the historical theme type, the historical time type and the historical processing aging data, obtaining the reach parameter prediction model for predicting the time type with the highest processing aging corresponding to the theme type according to the theme type.
Optionally, the target reach parameter obtaining unit 503 is specifically configured to obtain, according to the target topic type and the reach parameter prediction model, a target time type with the highest processing timeliness corresponding to the target topic type; the target reaching scheme comprises guiding information used for guiding the information to be sent to the target entity object at the target time corresponding to the target time type with the highest processing timeliness corresponding to the target theme type.
Optionally, the target access scheme further includes at least one of the following information: frequency information for guiding the information to be sent to the target entity object; and sending mode information used for guiding the information to be sent to the target entity object.
Optionally, the apparatus further comprises: and the sending unit is used for sending the information to be sent to the target entity object according to the target touch scheme.
Optionally, the information to be sent includes at least one of the following information: the user complains the information of the target entity object; query information of the user aiming at the target entity object; (ii) a receipt refund information for the target entity object; the information of the user for canceling the order of the target entity object; negative comment information of the user for the target entity object.
Third embodiment
Corresponding to the above method embodiments provided by the present application, a third embodiment of the present application further provides an electronic device. Since the third embodiment is substantially similar to the above method embodiment provided in this application, it is described relatively simply, and reference may be made to the description of the above method embodiment provided in this application for relevant points. The device embodiments described below are merely illustrative.
Fig. 6 is a schematic view of an electronic device provided in a third embodiment of the present application.
The electronic device includes:
a processor 601; and
a memory 602 for storing a program of the computer method, which when read and executed by the processor performs any of the methods described above.
It should be noted that, for the detailed description of the electronic device provided in the third embodiment of the present application, reference may be made to an application scenario of the reach scheme generation method provided in the present application and related descriptions of the foregoing method embodiments provided in the present application, and details are not repeated here.
Fourth embodiment
Corresponding to the above method embodiments provided in the present application, a fourth embodiment of the present application further provides a computer storage medium, and since the fourth embodiment is substantially similar to the above method embodiments provided in the present application, the description is relatively simple, and relevant points can be referred to the description of the above method embodiments provided in the present application. The fourth + embodiment described below is merely illustrative.
The computer storage medium stores a computer program that, when executed, implements the methods provided in the above-described method embodiments.
It should be noted that, for the detailed description of the storage medium provided in the tenth embodiment of the present application, reference may be made to the related description of the foregoing method embodiment provided in the present application, and details are not repeated here.
Although the present invention has been described with reference to the preferred embodiments, it should be understood that the scope of the present invention is not limited to the embodiments described above, and that various changes and modifications may be made by one skilled in the art without departing from the spirit and scope of the present invention.
In a typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
The memory may include forms of volatile memory in a computer readable medium, Random Access Memory (RAM) and/or non-volatile memory, such as Read Only Memory (ROM) or Flash memory (Flash RAM). Memory is an example of a computer-readable medium.
1. Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, computer readable Media does not include non-Transitory computer readable Media (transient Media), such as modulated data signals and carrier waves.
2. As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
Claims (15)
1. A reach plan generation method, comprising:
obtaining information to be sent which is to be sent to a target entity object and needs to be processed by the target entity object, wherein the target entity object is an entity object for providing service for a user;
obtaining a target subject type to which the target entity object belongs;
acquiring a target reach parameter corresponding to the target theme type according to the target theme type and a reach parameter prediction model, wherein the reach parameter prediction model is a model for predicting the reach parameter corresponding to the theme type according to the theme type;
and generating a target touch scheme for guiding the information to be sent to the target entity object according to the target touch parameter.
2. The method of claim 1, wherein the obtaining of the target subject type to which the target entity object belongs comprises: and inputting the identification information of the target entity object into a theme type prediction model for predicting the theme type to which the entity object belongs according to the identification information of the entity object to obtain the target theme type to which the target entity object belongs.
3. The method of claim 1, wherein the topic type prediction model is obtained by:
acquiring basic data of a historical entity object and historical processing data of information which is processed by the historical entity object and sent to the historical entity object;
obtaining historical characteristic data of the historical entity object according to the basic data of the historical entity object and the historical processing data of the historical entity object;
constructing a relation matrix between the identification information of the historical entity object and the historical characteristic data;
obtaining a relation matrix between the identification information of the historical entity object and the specified theme type according to the relation matrix between the identification information of the historical entity object and the historical characteristic data and the specified theme type;
and obtaining the theme type prediction model according to the relation matrix between the identification information of the historical entity object and the specified theme type.
4. The method of claim 3, wherein the underlying data of the historical entity object comprises at least one of:
type data of the historical entity object;
tag data of the historical entity object;
category data to which the historical entity object belongs;
service time data of the historical entity object;
service mode data of the historical entity object.
5. The method of claim 3, wherein the historical processing data of the historical entity object comprises at least one of:
the number of the information touched by the historical entity object in a preset time range;
reach time data of the reached information of the historical entity object;
the historical entity object responds to response time data of the touched information;
processing duration data of the touched information is processed by the historical entity object;
and the historical entity object processes the processing mode data of the touched information.
6. The method according to claim 3, wherein obtaining the relationship matrix between the identification information of the historical entity object and the specified topic type according to the relationship matrix between the identification information of the historical entity object and the historical feature data and the specified topic type comprises:
obtaining a relation matrix between the identification information of the historical entity object and the appointed initial theme type according to the relation matrix between the identification information of the historical entity object and the historical characteristic data and the appointed initial theme type;
if the relation matrix between the identification information of the historical entity object and the specified initial theme type does not meet the preset condition, adjusting the initial theme type to obtain the adjusted theme type;
obtaining a relation matrix between the identification information of the historical entity object and the adjusted subject type according to the relation matrix between the identification information of the historical entity object and the historical characteristic data and the adjusted initial subject type;
the obtaining the topic type prediction model according to the relationship matrix between the identification information of the historical entity object and the specified topic type includes: and obtaining the theme type prediction model according to the relation matrix between the identification information of the historical entity object and the adjusted theme type.
7. The method of claim 1, wherein the target topic type is one of the following topic types:
a service scale type of the target entity object;
a service feature type of the target entity object;
the response time type of the information that the response of the target entity object is touched;
and the target entity object processes the processing mode type of the touched information.
8. The method of claim 1, wherein the reach parameter prediction model is obtained by:
obtaining a history subject type to which a history entity object belongs;
obtaining historical processing aging data of the processed information of the historical entity object in different historical time types;
constructing a relation matrix among the historical theme type, the historical time type and the historical processing aging data;
and according to the relation matrix among the historical theme type, the historical time type and the historical processing aging data, obtaining the reach parameter prediction model for predicting the time type with the highest processing aging corresponding to the theme type according to the theme type.
9. The method according to claim 1, wherein the obtaining of the target reach parameter corresponding to the target topic type according to the target topic type and the reach parameter prediction model comprises:
acquiring a target time type with the highest processing timeliness corresponding to the target theme type according to the target theme type and the touch parameter prediction model;
the target reaching scheme comprises guiding information used for guiding the information to be sent to the target entity object at the target time corresponding to the target time type with the highest processing timeliness corresponding to the target theme type.
10. The method of claim 9, wherein the target access scheme further comprises at least one of:
frequency information for guiding the information to be sent to the target entity object;
and sending mode information used for guiding the information to be sent to the target entity object.
11. The method of claim 1, further comprising: and sending the information to be sent to the target entity object according to the target touch scheme.
12. The method of claim 1, wherein the information to be transmitted comprises at least one of the following information:
the user complains the information of the target entity object;
query information of the user aiming at the target entity object;
(ii) a receipt refund information for the target entity object;
the information of the user for canceling the order of the target entity object;
negative comment information of the user for the target entity object.
13. A reach plan generation apparatus, comprising:
a to-be-sent message obtaining unit, configured to obtain to-be-sent information to be sent to a target entity object and to be processed by the target entity object, where the target entity object is an entity object that provides a service for a user;
a target subject type obtaining unit, configured to obtain a target subject type to which the target entity object belongs;
a target reach parameter obtaining unit, configured to obtain a target reach parameter corresponding to the target topic type according to the target topic type and a reach parameter prediction model, where the reach parameter prediction model is a model used to predict a reach parameter corresponding to the topic type according to the topic type;
and the target touch scheme generating unit is used for generating a target touch scheme for guiding the information to be sent to the target entity object according to the target touch parameters.
14. An electronic device, comprising:
a processor; and
a memory for storing a computer program which, when the apparatus is powered on and the computer program is run by the processor, performs the method of any one of claims 1 to 12.
15. A storage medium, characterized in that the storage medium stores a computer program which is run by a processor for performing the method of any one of claims 1-12.
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