WO2018059122A1 - Service recommendation method, terminal, server, and storage medium - Google Patents

Abstract

A service recommendation method, comprising: obtaining a user identifier and corresponding user scenario information (S402); inquiring a user cluster to which the obtained user identifier belongs, the user cluster being obtained by clustering corresponding user identifiers according to personal service recommendation methods in a personal service recommendation method set of a multi-user source (S404); obtaining a universal cluster service recommendation method corresponding to the user cluster, the universal cluster service recommendation method being generated according to the personal service recommendation methods, in the personal service recommendation method set, corresponding to the user cluster (S406); and recommending service information, in the universal cluster service recommendation method, corresponding to the met triggering condition when the user scenario information meets a triggering condition in the universal cluster service recommendation method (S408).

Description

Service recommendation method, terminal, server, and storage medium

Cross-reference to related applications

The present application claims priority to the Chinese Patent Application, filed on Sep. 29, 2016, the entire disclosure of which is hereby incorporated by reference.

Technical field

The present application relates to the field of information processing technologies, and in particular, to a service recommendation method, a terminal, a server, and a storage medium.

Background technique

At present, recommending data to users mainly adopts data recommendation methods based on user preferences. In this way, it is necessary to collect a large number of historical behavior samples of the user, and analyze the user's preferences from a large number of historical behavior samples, thereby performing the analyzed preferences. Data recommendations to extend the user's source of information. For example, through the user's past product browsing record, product collection record or product purchase record, the user's preference can be analyzed, so that the product can be recommended to the user according to the preference.

However, at present, the recommended data needs to collect a large number of historical behavior samples of the user, so that the user's preferences can be analyzed comprehensively, and the historical behavior samples of the collected users are very limited, which leads to one-sided recommendation data, and it is difficult to ensure recommendation data. Richness.

Summary of the invention

According to various embodiments of the present application, a service recommendation method, a terminal, a server, and a storage medium are provided.

A service recommendation method is implemented on a server, the server includes a memory and a processor, and the method includes:

Obtaining a user identifier and corresponding user scene information;

Querying the user cluster to which the obtained user identifier belongs; the user cluster clusters the corresponding user identifier according to each user recommendation manner in the personal service recommendation method set of the multi-user source;

Obtaining a cluster general service recommendation manner corresponding to the user cluster; the cluster general service recommendation manner is generated according to the personal service recommendation manner corresponding to the user cluster in the personal service recommendation method set; and

When the user scenario information meets the triggering condition in the cluster general service recommendation mode, the service information corresponding to the met trigger condition in the cluster general service recommendation mode is recommended.

A service recommendation method is implemented in a terminal, where the terminal includes a memory and a processor, and the method includes:

Reporting the user identifier and the corresponding user scenario information to the server, so that the server queries the user cluster to which the reported user identifier belongs, and obtains the cluster general service recommendation mode corresponding to the user cluster, where the user scenario information meets the cluster common When the triggering condition in the service recommendation mode is used, the service information corresponding to the met trigger condition in the cluster general service recommendation mode is recommended; the user cluster according to the individual service recommendation manner in the personal service recommendation mode set of the multi-user source Corresponding user identifiers are obtained by clustering; the cluster general service recommendation manner is generated according to the personal service recommendation manner corresponding to the user cluster in the set of personal service recommendation manners;

Receiving the service information recommended by the server;

Displaying a notification interface, and displaying a corresponding service portal in the notification interface according to the service information.

A server comprising a memory and a processor, the memory storing computer readable instructions, the computer readable instructions being executed by the processor such that the processor performs the following steps:

Obtaining a user identifier and corresponding user scene information;

Querying the user cluster to which the obtained user identifier belongs; the user cluster clusters the corresponding user identifier according to each user recommendation manner in the personal service recommendation method set of the multi-user source;

Obtaining a cluster general service recommendation manner corresponding to the user cluster; the cluster general service recommendation manner is generated according to the personal service recommendation manner corresponding to the user cluster in the personal service recommendation method set; and

When the user scenario information meets the triggering condition in the cluster general service recommendation mode, the service information corresponding to the met trigger condition in the cluster general service recommendation mode is recommended.

A terminal comprising a memory and a processor, the memory storing computer readable instructions, the computer readable instructions being executed by the processor such that the processor performs the following steps:

Reporting the user identifier and the corresponding user scenario information to the server, so that the server queries the user cluster to which the reported user identifier belongs, and obtains the cluster general service recommendation mode corresponding to the user cluster, where the user scenario information meets the cluster common When the triggering condition in the service recommendation mode is used, the service information corresponding to the met trigger condition in the cluster general service recommendation mode is recommended; the user cluster according to the individual service recommendation manner in the personal service recommendation mode set of the multi-user source Corresponding user identifiers are obtained by clustering; the cluster general service recommendation manner is generated according to the personal service recommendation manner corresponding to the user cluster in the set of personal service recommendation manners;

Receiving the service information recommended by the server;

Displaying a notification interface, and displaying a corresponding service portal in the notification interface according to the service information.

A non-transitory computer readable storage medium storing computer readable instructions that, when executed by a processor, cause the processor to perform the steps of the service recommendation method.

Details of one or more embodiments of the present application are set forth in the accompanying drawings and description below. Other features, objects, and advantages of the invention will be apparent from the description and appended claims.

DRAWINGS

In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings to be used in the embodiments will be briefly described below. Obviously, the drawings in the following description are only some embodiments of the present application, Those skilled in the art can also obtain other drawings based on these drawings without any creative work.

1 is an application environment diagram of a service recommendation system in an embodiment;

2 is a schematic diagram showing the internal structure of a terminal in an embodiment;

3 is a schematic diagram showing the internal structure of a server in an embodiment;

4 is a schematic flow chart of a service recommendation method in an embodiment;

FIG. 5 is a schematic diagram of a process of clustering a user cluster, determining a cluster general service recommendation manner, and performing service recommendation in an embodiment;

6 is a schematic flow chart of a service recommendation method in another embodiment;

7 is a flow chart showing the steps of forming a personal service recommendation method in an embodiment;

8 is a flow chart showing the steps of forming a personal service recommendation method in another embodiment;

FIG. 9 is a schematic flowchart of a step of forming a trigger condition according to user behavior scene information and forming service information according to user behavior information in an embodiment; FIG.

10 is a schematic flowchart of a step of counting the number of user scene behavior records corresponding to the acquired user identifier and including user behavior scene information of the same type in a statistical time period in an embodiment;

11 is a schematic flow chart of a service recommendation method in another embodiment;

12 is a schematic diagram of a terminal display notification interface in an embodiment;

13 is a schematic diagram of a terminal display notification interface in another embodiment;

14 is a schematic diagram of a terminal display notification interface in still another embodiment;

15 is a schematic flowchart of a step of triggering user feedback and transmitting to a server, so that the server adjusts weight according to user feedback;

Figure 16 is a block diagram showing the structure of a server in an embodiment;

17 is a structural block diagram of a server in another embodiment;

18 is a structural block diagram of a terminal in an embodiment;

Figure 19 is a block diagram showing the structure of a terminal in another embodiment.

detailed description

In order to make the objects, technical solutions, and advantages of the present application more comprehensible, the present application will be further described in detail below with reference to the accompanying drawings and embodiments. It is understood that the specific embodiments described herein are merely illustrative of the application and are not intended to be limiting.

FIG. 1 is a diagram of an application environment of a service recommendation system in an embodiment. Referring to FIG. 1, the service recommendation system includes a terminal 110 and a server 120. The terminal 110 and the server 120 are connected through a network. The terminal 110 can be configured to report the user scene behavior record and the corresponding user identifier to the server 120. The server 120 is configured to obtain a user scene behavior record and a corresponding user identifier; the user scene behavior record includes user behavior information and corresponding user behavior scene information; the server 120 is configured to form a trigger condition according to the user behavior scene information, and form a service according to the user behavior information. Information; the server 120 is configured to associate the formed trigger condition with the formed service information to form a personal service recommender corresponding to the acquired user identifier. formula. The server 120 may specifically count the number of user scene behavior records corresponding to the acquired user identifier and including the user behavior scene information of the same type in the statistical time period; when the number of statistics in the statistical time period is higher than a preset threshold, according to the same type The user behavior scenario information forms a trigger condition, and the service information is formed according to the user behavior information corresponding to the user behavior scenario information of the same type.

In one embodiment, the user behavior scene information includes user behavior time and/or user behavior geographic location. The server 120 may be configured to generate a fuzzy range of the user behavior scene information included in each user scene behavior record corresponding to the acquired user identifier, and cluster the user behavior scene information in each user scene behavior record according to the corresponding fuzzy range, and determine to include the same type. The user scene behavior record of the user behavior scenario information; the number of user scene behavior records including the same user behavior scenario information is counted in the statistical time period.

In an embodiment, the terminal 110 may report the user identifier and the corresponding user scene information to the server 120. The server 120 may be configured to obtain the user identifier and the corresponding user scenario information; query the user cluster to which the obtained user identifier belongs; and the user cluster aggregates the corresponding user identifier according to each user service recommendation manner in the personal service recommendation mode set of the multi-user source. The server 120 can be configured to obtain a cluster general service recommendation mode corresponding to the user cluster; the cluster general service recommendation mode is generated according to the personal service recommendation manner corresponding to the user cluster in the personal service recommendation mode set; the server 120 can be configured to: when the user scenario information is satisfied. When the trigger condition in the cluster general service recommendation mode is used, the terminal 110 recommends the service information corresponding to the satisfied trigger condition in the cluster general service recommendation mode.

In an embodiment, the server 120 may specifically recommend the service information corresponding to the met trigger condition in the personal service recommendation mode when the user scenario information satisfies the trigger condition in the personal service recommendation manner corresponding to the acquired user identifier; When the scenario information does not meet the trigger condition in the personal service recommendation mode corresponding to the obtained user identifier, the user cluster to which the obtained user identifier belongs is queried.

In an embodiment, the server 120 may select a corresponding cluster general service recommendation manner according to the obtained weights corresponding to each cluster general service recommendation manner; the weight and the corresponding cluster general service recommendation manner are shared in the user cluster as the personal service recommendation manner. The number of users or the number of users is related; the service information corresponding to the triggered trigger condition in the recommended general service recommendation mode of the cluster is recommended.

In one embodiment, terminal 110 may report user feedback to the server 120 for the recommended service information. The server 120 may obtain user feedback for the recommended service information; The weight corresponding to the cluster general service recommendation method in which the recommended service information is adjusted is adjusted.

FIG. 2 is a schematic diagram showing the internal structure of a terminal in an embodiment. Referring to FIG. 2, the terminal includes a processor connected through a system bus, a non-volatile storage medium, an internal memory, a network interface, a display screen, and an input device. The non-volatile storage medium of the terminal stores an operating system, and can also store computer readable instructions. When the computer readable instructions are executed by the processor, the processor can implement a service recommendation method suitable for the terminal. The processor of the terminal is used to provide computing and control capabilities to support the operation of the entire terminal. Computer readable instructions may be stored in the internal memory in the terminal, the computer readable instructions being executable by the processor to cause the processor to perform a service recommendation method. The network interface of the terminal is used for network communication with the server, such as reporting the user identifier and corresponding user scene information, receiving the recommended service information, and the like. The display screen of the terminal may be a liquid crystal display or an electronic ink display screen, and the input device of the terminal may be a touch layer covered on the display screen, or a button, a trackball or a touchpad provided on the terminal housing, or may be an external connection. Keyboard, trackpad or mouse. The terminal can be a personal computer, a mobile terminal or a wearable device, such as a mobile phone, a tablet or a personal digital assistant. It will be understood by those skilled in the art that the structure shown in FIG. 2 is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the terminal to which the solution of the present application is applied. The specific terminal may include a ratio. More or fewer components are shown in Figure 2, or some components are combined, or have different component arrangements.

FIG. 3 is a schematic diagram showing the internal structure of a server in an embodiment. As shown in FIG. 3, the server includes a processor, a non-volatile storage medium, an internal memory, and a network interface connected by a system bus. The non-volatile storage medium of the server stores an operating system, and can also store computer readable instructions. When the computer readable instructions are executed by the processor, the processor can implement a service recommendation method suitable for the server. . The server's processor is used to provide computing and control capabilities that support the operation of the entire server. The computer's internal memory can store computer readable instructions that, when executed by the processor, cause the processor to perform a service recommendation method. The server's network interface is used to communicate with external terminals over a network connection. The server can be implemented with a stand-alone server or a server cluster consisting of multiple servers. Those skilled in the art can understand that the structure shown in FIG. 3 is only a block diagram of a partial structure related to the solution of the present application, and does not constitute a limitation on the server to which the solution of the present application is applied. The specific server may include a ratio. More or more There are few parts, or some parts are combined, or have different part arrangements.

4 is a schematic flow chart of a service recommendation method in an embodiment. The service recommendation method can be applied to the terminal 110 or the server 120. This embodiment is mainly applied to the server in FIG. 3 by using the method. Referring to FIG. 4, the service recommendation method in this embodiment specifically includes the following steps:

S402. Acquire a user identifier and corresponding user scene information.

The user identifier is used to uniquely identify the corresponding user. User information corresponding to the user scene is information indicating the scene in which the user is located. The user scene information may be user instant scene information. The user instant scene information is information indicating the immediate state of the scene in which the user is located. Instant refers to the current time or approximate current time. The user instant scene information may include a combination of one or more of user terminal instant time, user instant geographic location, or user immediate operation information.

The user terminal instant time refers to the instant time of the terminal logged in with the user ID. The real time of the user terminal can take different forms as needed, such as a form indicated by a date and a time point of the day, or a form represented only by the time point of the day. The user terminal's instant time can be accurate to hours or minutes or seconds or milliseconds.

The user's instant location is used to indicate the user's immediate location. The user's real-time location can be used in the location of the terminal, such as the longitude and latitude of the location of the terminal. The user's real-time geographic location can also adopt the information point (POI, full name of Point of Information) where the user or the terminal is located.

The user's real-time operation information is information that records the user's immediate operation on the terminal, such as the application identifier of the application currently being used on the terminal, the function identifier of the function being used in the application that the terminal is currently being used, and the data generated by the current operation. One or a combination of several.

S404: Query the user cluster to which the obtained user identifier belongs; the user cluster obtains the corresponding user identifier according to each user service recommendation manner in the personal service recommendation method set of the multi-user source.

The service recommendation method refers to the data on which the service recommendation is based, and may also be referred to as a service recommendation policy. The personal service recommendation method is a personal service recommendation method. The personal service recommendation method corresponds to the user identifier, and indicates that the user recommendation is performed by using the personal service recommendation method corresponding to the user identifier. The personal service recommendation method set is a multi-user source, indicating that the set includes more than one user's personal service recommendation method. Personal service recommendation methods include trigger conditions and corresponding The service information indicates that the service information corresponding to the trigger condition is recommended to the terminal corresponding to the corresponding user identifier when the trigger condition is met.

A user cluster is a collection of user IDs obtained by clustering. Clustering is the process of dividing objects into different subsets so that similar objects belong to the same subset. Referring to FIG. 5, each person service recommendation manner in the multi-user source personal service recommendation method set corresponds to a user identifier, and the user identifiers are clustered according to the similarity of the personal service recommendation manners to obtain more than one user cluster. The personal service recommendation methods corresponding to the user IDs in the same user cluster have similarities. The server may specifically cluster the individual service recommendation manners in the personal service recommendation method set into a personal service recommendation mode subset, and then configure the user identifier corresponding to each individual service recommendation mode subset to form a corresponding user cluster.

According to the personal service recommendation method in the personal service recommendation method set, clustering may be adopted, such as K-means clustering algorithm, artificial neural network algorithm or Support Vector Machine (SVM). When clustering, the personal service recommendation method in the personal service recommendation method set can be abstracted into a vector and then clustered. When using the K-means clustering algorithm, clustering can be performed as follows: (1) randomly select K cluster centers in the personal service recommendation method set; (2) traverse the personal service recommendation method set, and select the personal service recommendation method. The personal service recommendation method in the collection is divided into the nearest cluster center to get the corresponding cluster; (3) calculate the average value of each cluster and use it as a new cluster center; repeat (2) and (3) until it is satisfied. Iterative stop condition. The iteration stop condition is, for example, the maximum number of iterations, or the last calculated cluster center is smaller than the preset value of the cluster center calculated earlier than the preset value.

For example, if one of the personal service recommendation methods in the personal service recommendation method set is triggered by the noon time and/or the dinner time, the corresponding service information is the take-out application service information; in another personal service recommendation mode, The trigger condition is the working time period and/or the working time period, and the corresponding service information is the online car application service information. If the number of user identifiers corresponding to the two personal service recommendation methods exceeds a predetermined value, the user identifiers corresponding to the two personal service recommendation methods may be clustered into one user cluster, indicating a white-collar user group.

S406. Acquire a cluster general service recommendation mode corresponding to the user cluster. The cluster general service recommendation mode is generated according to the personal service recommendation manner corresponding to the user cluster in the personal service recommendation mode set.

The general service recommendation method of the cluster is to push the service identifier of the corresponding user cluster. The recommendation method of the service shared by the recommendation. The personal service recommendation method corresponding to the user cluster in the personal service recommendation method set refers to the personal service recommendation mode in the personal service recommendation method set corresponding to the user identifier in the user cluster.

The cluster general service recommendation method may specifically adopt all personal service recommendation methods corresponding to the user cluster in the personal service recommendation method set. In the personal service recommendation mode corresponding to the user cluster in the personal service recommendation mode set, the personal service recommendation mode in which the number of user identifiers in the corresponding user cluster is greater than the preset value is used as the cluster general service recommendation corresponding to the user cluster. the way. The cluster general service recommendation method may also be adjusted based on the personal service recommendation method corresponding to the user cluster in the personal service recommendation method set.

S408: When the user scenario information meets a trigger condition in the cluster general service recommendation mode, the service information corresponding to the met trigger condition in the cluster general service recommendation mode is recommended.

The cluster general service recommendation method includes a trigger condition and corresponding service information. For the user identifier of the user cluster, when the user scenario information corresponding to the user identifier meets the triggering conditions included in the cluster general service recommendation mode, the terminal corresponding to the user identifier is recommended to the cluster general service recommendation mode and the trigger. Service information corresponding to the condition. The service information is information that provides a service to the user, and may be information or a link, and the link may be a web link, a connection to open a specified application, or a connection to open a specified function of a specified application.

For example, the foregoing white-collar user group, if a large number of user identifiers (such as more than a predetermined number or a predetermined proportion of user identifiers), have the same or similar personal service recommendation methods, such as a trigger condition of Saturday or near Saturday, and The corresponding service information is a personal service recommendation method for the movie ticket purchase application service information. The personal service recommendation method may be used as a cluster general service recommendation mode of the white-collar user group. When the user terminal corresponding to any user identifier in the white-collar user group belongs to Saturday or near Saturday, the corresponding terminal is identified to the user. Recommend movie ticket purchase application service information.

After obtaining the user identifier and the corresponding user scenario information, the service recommendation method may query the user cluster to which the user identifier belongs, and the user cluster shall correspond to the user according to the individual service recommendation manner in the personal service recommendation method set of the multi-user source. The identifier is obtained by clustering, and then the user cluster represents a user group similar to the user indicated by the obtained user identifier in the personal service recommendation manner. The cluster general service recommendation method corresponding to the user cluster is based on the collection of personal service recommendation methods. The personal service recommendation manner corresponding to the user cluster is generated, so that the individual service recommendation manner can be used in the user cluster. When the user scenario information meets the triggering conditions in the cluster general service recommendation mode, the service information corresponding to the met trigger condition in the general service recommendation mode of the cluster is recommended to avoid the one-sided recommendation service information and ensure the richness of the recommended service information.

In an embodiment, after the step S402, the service recommendation method further includes: when the user scenario information meets a trigger condition in the personal service recommendation manner corresponding to the acquired user identifier, recommending the trigger in the personal service recommendation manner and the satisfaction The service information corresponding to the condition; when the user scenario information does not satisfy the trigger condition in the personal service recommendation mode corresponding to the acquired user identifier, step S404 is performed.

Specifically, referring to FIG. 6, after obtaining the user identifier and the corresponding user scene information, the server may first determine whether the user scene information meets the trigger condition in the personal service recommendation manner corresponding to the user identifier. When the trigger condition in the personal service recommendation mode is met, the server may directly identify the service information corresponding to the satisfied trigger condition in the personal service recommendation mode of the corresponding terminal recommendation. The server may further determine whether the user scenario information meets the triggering condition in the cluster general service recommendation mode corresponding to the user cluster to which the user identifier belongs, when the triggering condition in the user service recommendation mode is not met.

When the triggering condition in the cluster general service recommendation mode corresponding to the user cluster to which the user ID belongs is met, the server may identify the service information corresponding to the met trigger condition in the recommended general service recommendation mode of the terminal. When the trigger condition in the cluster general service recommendation mode corresponding to the user cluster to which the user ID belongs is not satisfied, or after the service information is recommended, the server may record the user scenario information as the user behavior scenario information. After recommending the service information to the terminal, the server may receive user feedback of the user terminal for the service information.

In this embodiment, the service recommendation is preferentially performed according to the personal service recommendation method, and the accuracy of the service recommendation may be preferentially ensured; if the service recommendation is not performed according to the cluster general service recommendation method when the service recommendation cannot be performed according to the service recommendation mode, the user may be recommended. Service information for potential needs to meet user needs as much as possible.

In one embodiment, the service recommendation method further includes the step of forming a personal service recommendation method. As shown in FIG. 7 and FIG. 8 , the step of forming a personal service recommendation manner specifically includes the following steps:

S702. Acquire a user scene behavior record and a corresponding user identifier. The user scene behavior record includes user behavior information and corresponding user behavior scene information.

The user scene behavior record is data that records the behavior of the user in a specific scenario. User behavior can be the behavior of the user operating the terminal. The user scene behavior record may be generated by the user scene information and user feedback reported by the user terminal, or may be directly reported to the server by the user terminal. The user scene behavior record may include user behavior scene information and corresponding user behavior information, and the user behavior scene information includes user behavior time and/or user behavior geographic location. The user behavior time can indicate the time when the user behavior occurs, and the user behavior geographic location can indicate the geographic location where the user behavior occurs. The user scene behavior record can include a user behavior track. The user behavior track can represent the order in which multiple user actions occur.

For example, a user scene behavior record can be recorded as: 2016-8-19, 19:32, Shenzhen Science and Technology Park XX Cafe, XX Cafe Member Application - Membership Card. The user scene behavior record can indicate that the user performed the user behavior time at 19:32 on August 19, 2016, and implemented the user in the XX Cafe Member Application at the location of the user behavior of the Shenzhen Science and Technology Park XX Cafe. Card features this user behavior.

For another example, a user scene behavior record can be recorded as: Service A, Service B. The user scene behavior record indicates that the user has used service B after using service A. The user scene behavior record represents a user behavior track.

S704. Form a trigger condition according to the user behavior scenario information, and form service information according to the user behavior information.

Specifically, the server may directly form the trigger condition for the user behavior scenario information, such as the user behavior time and/or the user behavior geographic location to form a trigger condition. The user behavior that occurs first in the user behavior track can be regarded as the user behavior scene information, and the user behavior that occurs later can be regarded as the user behavior information. When the user behavior record records the user behavior track, the user behavior occurring in the user behavior track may be triggered, and the user behavior occurring in the user behavior track forms service information corresponding to the trigger condition.

S706: Correspond to the formed service information, and form a personal service recommendation manner corresponding to the acquired user identifier.

In this embodiment, the personal service recommendation mode is generated by using the user scene behavior record, and the service recommendation can be accurately performed based on the personal service recommendation mode, and the service recommendation accuracy is improved.

Referring to FIG. 9, in an embodiment, step S704 specifically includes the following steps:

S902. Count, in the statistical time period, the number of user scene behavior records corresponding to the acquired user identifier and including the same type of user behavior scene information.

The statistical time period may be a preset number of days, specifically one week or one month, and an appropriate statistical time period may be selected according to the accuracy requirement of the service recommendation. The same kind of user behavior scene information is the same or similar user behavior scene information, for example, the user behavior time difference is within a preset range, or the user behavior geographical position is within a preset range. The same kind of user behavior scene information may also include the same user behavior track segment, and the user behavior track segment is a part of the user behavior track intercepted.

For example, suppose there are three user scene behavior records, which are scene A-service A, scene B-service B, and scene C-service C. If scenes A, B, and C are the same or very close, scenes A, B, and C For the same user behavior scenario information, the three user scene behavior records can be recorded as the same user scene behavior record statistics.

S904: When the number of statistics in the statistical period is higher than the preset threshold, the triggering condition is formed according to the user behavior scenario information of the same type, and the service information is formed according to the user behavior information corresponding to the user behavior scenario information of the same type.

Specifically, the preset threshold can be set as needed. The server can form a trigger condition that can simultaneously satisfy the same kind of user behavior scene information. The server may form service information capable of covering user behavior information corresponding to user behavior scenario information of the same type.

In this embodiment, the personal service recommendation manner is formed according to a large number of user scene behavior records in the user scene behavior record including the user behavior scene information of the same type, so that the personal service recommendation manner can accurately reflect the user's service recommendation requirement. Regardless of the service recommendation based on the personal service recommendation method or the service recommendation based on the cluster general service recommendation method, certain accuracy can be guaranteed.

In one embodiment, the user behavior scenario information includes a user behavior time and/or a user behavior geographic location; referring to FIG. 10, step S902 includes the following steps:

S1002: Generate a fuzzy range of user behavior scene information included in each user scene behavior record corresponding to the acquired user identifier.

Specifically, the server may obtain all user scene behavior records corresponding to the user identifier, and generate The user behavior time and/or the fuzzy range of the user behavior geographic location included in each user scene behavior record. The fuzzy range refers to a range obtained by expanding the range based on the user behavior scene information. The fuzzy range of the user's behavior time, such as the scope extended by the user's behavior time, such as the user behavior time is 9:00, and the expansion range is 9:00 from 9:00 to the center. 10:00. Similarly, the fuzzy range of the geographic location may be a range formed by expanding the range centered on the user's behavioral geographic location.

S1004: The user behavior scene information in each user scene behavior record is clustered according to a corresponding fuzzy range, and the user scene behavior record including the same user behavior scene information is determined.

Specifically, the user behavior scene information is clustered according to the fuzzy range, and the user behavior scene information having the intersection or the intersection area larger than the preset area may be clustered into the same type, thereby determining the user including the same type of user behavior scene information. Scene behavior record.

S1006: Counts the number of user scene behavior records including the same user behavior scenario information in the statistical time period.

In this embodiment, the user behavior record including the same user behavior scene information is determined by using the user behavior time and/or the fuzzy range of the user behavior geographic location, so that the user scene behavior record can be generated more effectively, and the user behavior scene information is avoided. Specifically, the number of user scene behavior records is too small.

In an embodiment, the step of recommending the service information corresponding to the met triggering condition in the cluster general service recommendation mode in step S408 specifically includes: selecting a corresponding cluster general service recommendation manner according to the weights corresponding to the acquired general service recommendation manners of each cluster. The weight and the corresponding cluster general service recommendation method are related to the number of users or the number of users shared in the user cluster as the personal service recommendation method; the service information corresponding to the satisfied trigger condition in the recommended general service recommendation mode of the cluster is recommended.

Specifically, the user cluster may correspond to a plurality of cluster general service recommendation manners, and each cluster general service recommendation manner has a weight, and when the service recommendation is performed, a cluster general service recommendation manner may be selected from multiple cluster general service recommendation manners according to the weight. Service recommendation. The server may determine the probability of each general service recommendation mode according to the weight, thereby selecting the cluster general service recommendation mode according to the probability. The server can also directly select the cluster general service recommendation method with the largest weight to perform service recommendation. When the weights are the same, the server can randomly select from the cluster general service recommendation methods with the same weight.

The weight of the cluster general service recommendation method corresponding to the weight may be positively related to the number of users or the number of users shared in the user cluster as the personal service recommendation method, and may of course be negative correlation. Assume that the white-collar user group includes User A, User B, User C, and User D, and the cluster general service recommendation methods corresponding to the white-collar user group are E and F. The general service recommendation mode E of the cluster is the personal service recommendation mode common to the user A, the user B, and the user C, and the cluster general service recommendation mode F is only the personal service recommendation mode of the user A and the user B, and the weight of the E is higher than F. The weight of the server will be prioritized based on the cluster general service recommendation method E with high weight.

In this embodiment, the service recommendation is selected according to the weight of the cluster general service recommendation mode, and the appropriate cluster general service recommendation mode is selected for service recommendation when there are multiple cluster general service recommendation modes, and the service recommendation can satisfy the service requirement of the user as much as possible. .

In an embodiment, the step of recommending the service information corresponding to the met trigger condition in the personal service recommendation manner includes: selecting a corresponding personal general service recommendation manner according to the weight corresponding to each individual general service recommendation manner; and recommending the selected personal universal service The service information corresponding to the satisfied trigger condition in the recommended mode. The weight may be related to the number of user scene behavior records that correspond to the acquired user identification and including the same type of user behavior scene information within the statistical time period.

In an embodiment, the service recommendation method further includes: obtaining user feedback for the recommended service information; and adjusting a weight corresponding to the cluster general service recommendation manner in which the recommended service information is located according to the user feedback.

The user feedback may indicate acceptance of the service information or rejection of the service information. When the user feedback indicates that the service information is accepted, the server may increase the weight corresponding to the cluster general service recommendation mode in which the recommended service information is located. When the user feedback indicates that the service information is denied, the server may lower the weight corresponding to the cluster general service recommendation mode in which the recommended service information is located.

In this embodiment, the weight corresponding to the cluster general service recommendation mode can be adjusted through user feedback, so that the service recommendation policy can be dynamically adjusted to meet the user's changing service requirements.

11 is a schematic flow chart of a service recommendation method in another embodiment. This embodiment is mainly illustrated by applying the method to the terminal in FIG. 2 described above. Referring to FIG. 11, the method specifically includes the following steps:

S1102: Reporting the user identifier and the corresponding user scenario information to the server, so that the server queries the user cluster to which the reported user identifier belongs, and obtains the cluster general service recommendation manner corresponding to the user cluster. When the user scenario information meets the trigger condition in the cluster general service recommendation mode, the service information corresponding to the met trigger condition in the cluster general service recommendation mode is recommended; the user cluster is served according to the individual service recommendation mode set of the multi-user source. The recommended method is to cluster the corresponding user identifiers; the cluster general service recommendation method is generated according to the personal service recommendation manner corresponding to the user cluster in the personal service recommendation method set.

S1104: Receive service information recommended by the server.

S1106: Display a notification interface, and display a corresponding service entry in the notification interface according to the service information.

The notification interface may be generated by a notification channel provided by the terminal operating system, such as a drop-down notification bar or a top notification bar. The service information can include a link that the terminal can display as a service portal. The service entry is used to trigger a call to the corresponding service. The terminal may detect a user operation instruction for the service portal, and trigger a service pointed to by the service entry when detecting the user operation instruction, such as opening an application providing the service, or opening a specified function in the service, or linking to a specified webpage or the like.

After obtaining the user identifier and the corresponding user scenario information, the service recommendation method may query the user cluster to which the user identifier belongs, and the user cluster shall correspond to the user according to the individual service recommendation manner in the personal service recommendation method set of the multi-user source. The identifier is obtained by clustering, and then the user cluster represents a user group similar to the user indicated by the obtained user identifier in the personal service recommendation manner. The cluster general service recommendation method corresponding to the user cluster is generated according to the personal service recommendation manner corresponding to the user cluster in the personal service recommendation method set, so that the individual service recommendation manner can be common in the user cluster. When the user scenario information meets the triggering conditions in the cluster general service recommendation mode, the service information corresponding to the met trigger condition in the general service recommendation mode of the cluster is recommended to avoid the one-sided recommendation service information and ensure the richness of the recommended service information.

In an embodiment, the step S1102 includes: reporting the user identifier and the corresponding user scene information to the server, so that the server recommends the personal service recommendation when the user scene information meets the trigger condition in the personal service recommendation manner corresponding to the reported user identifier. The service information corresponding to the triggered triggering condition in the mode; when the user scenario information does not meet the triggering condition in the personal service recommendation manner corresponding to the reported user identifier, querying the user cluster to which the reported user identifier belongs, and acquiring the user cluster corresponding to the user cluster In the cluster general service recommendation mode, when the user scenario information meets the trigger condition in the cluster general service recommendation mode, the service information corresponding to the met trigger condition in the cluster general service recommendation mode is recommended.

For example, referring to FIG. 12, when the terminal uses the image editing application, the terminal reports the image editing application identifier and the user identifier to the server, and the server has a personal service recommendation manner indicating the user behavior track corresponding to the user identifier, and the service is provided. When the triggering condition of the recommended mode is the image editing application identifier, the image sharing application identifier corresponding to the triggering condition is obtained from the service recommendation mode to the terminal. The terminal displays a notification interface, and a service portal for entering the picture sharing application is displayed in the notification interface.

Referring to FIG. 13, the terminal may further receive service information that is sent by the server according to the instant time of the user terminal, and display a notification interface on the desktop of the terminal operating system, where the service portal is displayed. Referring to FIG. 14 , the service information may be recommended by the server according to the cluster general service recommendation manner of the personal service recommendation manner that is not corresponding to the user identifier, and after receiving the service information, the terminal may prompt the service information according to the individual not corresponding to the user identifier. The recommended general service recommendation method for the service recommendation method is recommended.

In an embodiment, the recommended service information is included in the cluster general service recommendation mode selected according to the weights corresponding to the acquired cluster general service recommendation manners. Referring to FIG. 15, the method further includes the steps of: triggering user feedback and sending to the server, so that the server adjusts the weight according to the user feedback, specifically including the following steps:

S1502: Display a service cancellation control in the notification interface according to the service information.

S1504: When detecting a user operation instruction for the service entry, enter an application pointed to by the service entry.

S1506: When detecting a user operation instruction for the service portal or the service cancellation control, send user feedback to the server, so that the server adjusts the weight corresponding to the cluster general service recommendation manner in which the recommended service information is located according to the user feedback.

Specifically, when detecting the user operation instruction for the service portal, the terminal generates user feedback indicating that the service information is accepted and sends the message to the server; when the terminal detects the user operation instruction for the service portal or the service cancellation control, the terminal generates a service denial service. The user of the information is fed back to the server, so that the server adjusts the weight corresponding to the cluster general service recommendation method according to the user feedback according to the user feedback.

In this embodiment, the weight corresponding to the cluster general service recommendation mode can be adjusted by user feedback. This allows the service recommendation policy to be dynamically adjusted to meet the changing service needs of users.

Figure 16 is a block diagram showing the structure of the server 1600 in one embodiment. The internal structure of the server 1600 may correspond to the structure as shown in FIG. 3, and each of the following modules may be implemented in whole or in part by software, hardware, or a combination thereof.

Referring to FIG. 16, the server 1600 includes: a data acquisition module 1601, a cluster general service recommendation mode acquisition module 1602, and a service information recommendation module 1603.

The data obtaining module 1601 is configured to obtain a user identifier and corresponding user scene information.

The cluster general service recommendation mode obtaining module 1602 is configured to query the user cluster to which the obtained user identifier belongs; obtain the cluster general service recommendation mode corresponding to the user cluster; and the user cluster recommends each person in the personal service recommendation mode set according to the multi-user source. The method comprises: clustering the corresponding user identifiers; the cluster general service recommendation manner is generated according to the personal service recommendation manner corresponding to the user cluster in the personal service recommendation method set;

The service information recommendation module 1603 is configured to recommend service information corresponding to the met trigger condition in the general service recommendation mode of the cluster when the user scenario information meets the trigger condition in the cluster general service recommendation mode.

In an embodiment, the service information recommendation module 1603 is further configured to: when the user scenario information meets a trigger condition in the personal service recommendation manner corresponding to the acquired user identifier, recommend a service corresponding to the met trigger condition in the personal service recommendation manner. information.

The cluster general service recommendation manner obtaining module 1602 is further configured to query the user cluster to which the obtained user identifier belongs when the user scenario information does not meet the trigger condition in the personal service recommendation manner corresponding to the obtained user identifier.

Figure 17 is a block diagram showing the structure of a server 1600 in another embodiment. Referring to FIG. 17, the server 1600 further includes: a personal service recommendation manner generating module 1604, configured to acquire a user scene behavior record and a corresponding user identifier; the user scene behavior record includes user behavior information and corresponding user behavior scene information; The information forming trigger condition is formed according to the user behavior information; the formed trigger condition is corresponding to the formed service information, and the personal service recommendation manner corresponding to the acquired user identifier is formed.

In one embodiment, the personal service recommendation method generation module 1604 is further configured to use the statistical time period. Counting the number of user scene behavior records corresponding to the obtained user identifiers and including the user behavior scene information of the same type; when the number of statistics in the statistical period is higher than the preset threshold, the trigger condition is formed according to the similar user behavior scene information, according to User behavior information corresponding to similar user behavior scenario information forms service information.

In one embodiment, the user behavior scenario information includes a user behavior time and/or a user behavior geographic location; the personal service recommendation manner generating module 1604 is further configured to generate a user behavior scenario included in each user scenario behavior record corresponding to the acquired user identifier. The fuzzy range of the information; the user behavior scene information in each user scene behavior record is clustered according to the corresponding fuzzy range, and the user scene behavior record including the same user behavior scene information is determined; the statistics include the same type of user behavior in the statistical time period. The number of user scene behavior records for scene information.

In an embodiment, the service information recommendation module 1603 is further configured to select a corresponding cluster general service recommendation manner according to the weights corresponding to the obtained cluster common service recommendation manners; the weight and the corresponding cluster general service recommendation manner are used as the personal service recommendation manner. The number of users or the number of users shared in the user cluster is related; the service information corresponding to the triggered trigger condition in the recommended general service recommendation mode of the cluster is recommended.

In an embodiment, the server 1600 further includes: a weight adjustment module 1605, configured to obtain user feedback for the recommended service information; and adjust a weight corresponding to the cluster general service recommendation manner in which the recommended service information is located according to the user feedback.

After obtaining the user identifier and the corresponding user scenario information, the server 1600 can query the user cluster to which the user identifier belongs, and the user cluster associates the corresponding user identifier according to each user recommendation manner in the personal service recommendation method set of the multi-user source. Clustering is performed, so that the user cluster represents a user group similar to the user indicated by the obtained user identifier in the personal service recommendation manner. The cluster general service recommendation method corresponding to the user cluster is generated according to the personal service recommendation manner corresponding to the user cluster in the personal service recommendation method set, so that the individual service recommendation manner can be common in the user cluster. When the user scenario information meets the triggering conditions in the cluster general service recommendation mode, the service information corresponding to the met trigger condition in the general service recommendation mode of the cluster is recommended to avoid the one-sided recommendation service information and ensure the richness of the recommended service information.

FIG. 18 is a block diagram showing the structure of a terminal 1800 in an embodiment. The internal structure of the terminal 1800 can correspond to In the structure shown in FIG. 2, each of the following modules may be implemented in whole or in part by software, hardware, or a combination thereof.

Referring to FIG. 18, the terminal 1800 includes: a reporting module 1801, a service information receiving module 1802, and a notification interface displaying module 1803.

The reporting module 1801 is configured to report the user identifier and the corresponding user scenario information to the server, so that the server queries the user cluster to which the reported user identifier belongs, and obtains the cluster general service recommendation mode corresponding to the user cluster, and the user scenario information satisfies the cluster general service recommendation. In the triggering condition of the mode, the service information corresponding to the met trigger condition in the cluster general service recommendation mode is recommended; the user cluster aggregates the corresponding user identifier according to each person service recommendation manner in the personal service recommendation mode set of the multi-user source. The class general service recommendation method is generated according to the personal service recommendation method corresponding to the user cluster in the personal service recommendation method set.

The service information receiving module 1802 is configured to receive service information recommended by the server.

The notification interface display module 1803 is configured to display a notification interface, and display a corresponding service portal in the notification interface according to the service information.

In an embodiment, the reporting module 1801 is further configured to report the user identifier and the corresponding user scenario information to the server, so that the server recommends the user when the user scenario information meets a trigger condition in the personal service recommendation manner corresponding to the reported user identifier. The service information corresponding to the triggered triggering condition in the service recommendation mode; when the user scenario information does not meet the triggering condition in the personal service recommendation manner corresponding to the reported user identifier, querying the user cluster to which the reported user identifier belongs, and acquiring the user cluster The corresponding general service recommendation mode of the cluster, when the user scenario information meets the trigger condition in the general service recommendation mode of the cluster, the service information corresponding to the met trigger condition in the general service recommendation mode of the cluster is recommended.

In an embodiment, the recommended service information is included in the cluster general service recommendation mode selected according to the weights corresponding to the acquired cluster general service recommendation manners.

The notification interface display module 1803 is further configured to display the service cancellation control in the notification interface according to the service information.

Referring to FIG. 19, the terminal 1800 further includes an application invoking module 1804 and a user feedback transmitting module 1805.

The application invoking module 1804 is configured to enter an application pointed to by the service portal when a user operation instruction for the service portal is detected.

The user feedback sending module 1805 is configured to send user feedback to the server when detecting a user operation instruction for the service portal or the service cancellation control, so that the server adjusts the cluster general service recommendation manner corresponding to the recommended service information according to the user feedback. Weights.

After obtaining the user identifier and the corresponding user scenario information, the server 1600 can query the user cluster to which the user identifier belongs, and the user cluster associates the corresponding user identifier according to each user recommendation manner in the personal service recommendation method set of the multi-user source. Clustering is performed, so that the user cluster represents a user group similar to the user indicated by the obtained user identifier in the personal service recommendation manner. The cluster general service recommendation method corresponding to the user cluster is generated according to the personal service recommendation manner corresponding to the user cluster in the personal service recommendation method set, so that the individual service recommendation manner can be common in the user cluster. When the user scenario information meets the triggering conditions in the cluster general service recommendation mode, the service information corresponding to the met trigger condition in the general service recommendation mode of the cluster is recommended to avoid the one-sided recommendation service information and ensure the richness of the recommended service information.

A person skilled in the art can understand that all or part of the process of implementing the above embodiment method can be completed by a computer program to instruct related hardware, and the program can be stored in a non-volatile computer readable storage medium. The program, when executed, may include the flow of an embodiment of the methods as described above. The storage medium may be a magnetic disk, an optical disk, a read-only memory (ROM), or the like.

The technical features of the above embodiments may be arbitrarily combined. For the sake of brevity of description, all possible combinations of the technical features in the above embodiments are not described. However, as long as there is no contradiction in the combination of these technical features, It is considered to be the range described in this specification.

The above embodiments are merely illustrative of several embodiments of the present application, and the description thereof is more specific and detailed, but is not to be construed as limiting the scope of the invention. It should be noted that a number of variations and modifications may be made by those skilled in the art without departing from the spirit and scope of the present application. Therefore, the scope of the invention should be determined by the appended claims.

Claims (21)

1. A service recommendation method is implemented on a server, the server includes a memory and a processor, and the method includes:

   Obtaining a user identifier and corresponding user scene information;

   Querying the user cluster to which the obtained user identifier belongs; the user cluster clusters the corresponding user identifier according to each user recommendation manner in the personal service recommendation method set of the multi-user source;

   Obtaining a cluster general service recommendation manner corresponding to the user cluster; the cluster general service recommendation manner is generated according to the personal service recommendation manner corresponding to the user cluster in the personal service recommendation method set; and

   When the user scenario information meets the triggering condition in the cluster general service recommendation mode, the service information corresponding to the met trigger condition in the cluster general service recommendation mode is recommended.
2. The method according to claim 1, wherein after the step of acquiring the user identifier and the corresponding user scene information, the method comprises:

   When the user scenario information meets a trigger condition in the personal service recommendation manner corresponding to the obtained user identifier, the service information corresponding to the satisfied trigger condition in the personal service recommendation manner is recommended;

   And the step of performing the user cluster to which the user identifier acquired by the query belongs is performed when the user scenario information does not meet the triggering condition in the personal service recommendation manner corresponding to the obtained user identifier.
3. The method of claim 1 further comprising:

   Obtaining a user scene behavior record and a corresponding user identifier; the user scene behavior record includes user behavior information and corresponding user behavior scene information;

   Forming a trigger condition according to the user behavior scenario information, and forming service information according to the user behavior information; and

   The generated trigger condition is associated with the formed service information to form a personal service recommendation manner corresponding to the acquired user identifier.
4. The method of claim 3, wherein said according to said user behavior field The scene information forms a trigger condition, and forming the service information according to the user behavior information includes:

   Counting, in the statistical time period, the number of user scene behavior records corresponding to the obtained user identifier and including the same type of user behavior scene information; and

   When the number of statistics in the statistical period is higher than the preset threshold, the triggering condition is formed according to the user behavior scenario information of the same type, and the service information is formed according to the user behavior information corresponding to the user behavior scenario information of the same type. .
5. The method according to claim 4, wherein the user behavior scenario information comprises a user behavior time and/or a user behavior geographic location; and the statistically corresponding to the acquired user identifier and includes the same type in the statistical time period The number of user scene behavior records for user behavior scenario information includes:

   Generating a fuzzy range of the user behavior scene information included in each user scene behavior record corresponding to the obtained user identifier;

   The user behavior scene information in each user scene behavior record is clustered according to the corresponding fuzzy range, and the user scene behavior record including the same user behavior scene information is determined;

   The number of user scene behavior records including the user behavior scene information of the same type is counted in the statistical time period.
6. The method according to claim 1, wherein the recommended service information corresponding to the met trigger condition in the cluster general service recommendation manner comprises:

   The corresponding cluster general service recommendation mode is selected according to the weights corresponding to the obtained general service recommendation manners of the clusters; the weights and the corresponding cluster general service recommendation manners are used as the number of users or users shared by the user cluster in the user service recommendation manner. Number of proportions; and

   The service information corresponding to the triggered trigger condition in the recommended general service recommendation mode of the cluster is recommended.
7. The method of claim 6 wherein the method further comprises:

   Obtaining user feedback for the recommended service information; and

   Adjusting, according to the user feedback, a weight corresponding to the cluster general service recommendation manner in which the recommended service information is located.
8. A service recommendation method is implemented in a terminal, where the terminal includes a memory and a processor, and the method includes:

   Reporting the user identifier and the corresponding user scenario information to the server, so that the server queries the user cluster to which the reported user identifier belongs, and obtains the cluster general service recommendation mode corresponding to the user cluster, where the user scenario information meets the cluster common When the triggering condition in the service recommendation mode is used, the service information corresponding to the met trigger condition in the cluster general service recommendation mode is recommended; the user cluster according to the individual service recommendation manner in the personal service recommendation mode set of the multi-user source Corresponding user identifiers are obtained by clustering; the cluster general service recommendation manner is generated according to the personal service recommendation manner corresponding to the user cluster in the set of personal service recommendation manners;

   Receiving the service information recommended by the server;

   Displaying a notification interface, and displaying a corresponding service portal in the notification interface according to the service information.
9. The method according to claim 8, wherein the reporting the user identifier and the corresponding user scenario information to the server, so that the server queries the user cluster to which the reported user identifier belongs, and obtains the cluster common to the user cluster. The service recommendation mode, when the user scenario information meets the triggering condition in the cluster general service recommendation mode, the recommended service information corresponding to the met trigger condition in the cluster general service recommendation mode is:

   Reporting the user identifier and the corresponding user scenario information to the server, so that the server recommends the personal service recommendation manner when the user scenario information meets a trigger condition in the personal service recommendation manner corresponding to the reported user identifier The service information corresponding to the met trigger condition; when the user scenario information does not meet the trigger condition in the personal service recommendation manner corresponding to the reported user identifier, querying the user cluster to which the reported user identifier belongs, acquiring the The cluster general service recommendation mode corresponding to the user cluster, when the user scenario information satisfies the trigger condition in the cluster general service recommendation mode, the service information corresponding to the met trigger condition in the cluster general service recommendation mode is recommended.
10. The method according to claim 8, wherein the recommended service information is included in the cluster general service push selected according to the weights corresponding to the acquired cluster general service recommendation manners. Recommended method; the method further includes:

    Displaying a service cancellation control in the notification interface according to the service information;

    Entering an application pointed to by the service portal when a user operation instruction for the service portal is detected;

    Sending user feedback to the server when detecting a user operation instruction for the service portal or the service cancellation control, so that the server adjusts the recommended cluster general service where the service information is recommended according to the user feedback The weight corresponding to the recommended method.
11. A server comprising a memory and a processor, the memory storing computer readable instructions, the computer readable instructions being executed by the processor such that the processor performs the following steps:

    Obtaining a user identifier and corresponding user scene information;

    Querying the user cluster to which the obtained user identifier belongs; the user cluster clusters the corresponding user identifier according to each user recommendation manner in the personal service recommendation method set of the multi-user source;

    Obtaining a cluster general service recommendation manner corresponding to the user cluster; the cluster general service recommendation manner is generated according to the personal service recommendation manner corresponding to the user cluster in the personal service recommendation method set; and

    When the user scenario information meets the triggering condition in the cluster general service recommendation mode, the service information corresponding to the met trigger condition in the cluster general service recommendation mode is recommended.
12. The server according to claim 11, wherein said computer readable instructions further cause said processor to perform the following steps after said step of obtaining a user identification and corresponding user scene information:

    When the user scenario information meets a trigger condition in the personal service recommendation manner corresponding to the obtained user identifier, the service information corresponding to the satisfied trigger condition in the personal service recommendation manner is recommended;

    And the step of performing the user cluster to which the user identifier acquired by the query belongs is performed when the user scenario information does not meet the triggering condition in the personal service recommendation manner corresponding to the obtained user identifier.
13. The server of claim 11 wherein said computer readable instructions further cause said processor to perform the following steps:

    Obtaining a user scene behavior record and a corresponding user identifier; the user scene behavior record includes user behavior information and corresponding user behavior scene information;

    Forming a trigger condition according to the user behavior scenario information, and forming service information according to the user behavior information; and

    The generated trigger condition is associated with the formed service information to form a personal service recommendation manner corresponding to the acquired user identifier.
14. The server according to claim 13, wherein the forming a trigger condition according to the user behavior scenario information, and forming the service information according to the user behavior information comprises:

    Counting, in the statistical time period, the number of user scene behavior records corresponding to the obtained user identifier and including the same type of user behavior scene information; and

    When the number of statistics in the statistical period is higher than the preset threshold, the triggering condition is formed according to the user behavior scenario information of the same type, and the service information is formed according to the user behavior information corresponding to the user behavior scenario information of the same type. .
15. The server according to claim 14, wherein the user behavior scenario information includes a user behavior time and/or a user behavior geographic location; and the statistically corresponding to the acquired user identifier and includes the same type in the statistical time period The number of user scene behavior records for user behavior scenario information includes:

    Generating a fuzzy range of the user behavior scene information included in each user scene behavior record corresponding to the obtained user identifier;

    The user behavior scene information in each user scene behavior record is clustered according to the corresponding fuzzy range, and the user scene behavior record including the same user behavior scene information is determined;

    The number of user scene behavior records including the user behavior scene information of the same type is counted in the statistical time period.
16. The server according to claim 11, wherein the recommended service information corresponding to the triggered trigger condition in the cluster general service recommendation manner comprises:

    The corresponding cluster general service recommendation mode is selected according to the weights corresponding to the obtained general service recommendation manners of the clusters; the weights and the corresponding cluster general service recommendation manners are used as the number of users or users shared by the user cluster in the user service recommendation manner. Number of proportions; and

    The service information corresponding to the triggered trigger condition in the recommended general service recommendation mode of the cluster is recommended.
17. The server of claim 16 wherein said computer readable instructions further cause said processor to perform the steps of:

    Obtaining user feedback for the recommended service information; and

    Adjusting, according to the user feedback, a weight corresponding to the cluster general service recommendation manner in which the recommended service information is located.
18. A terminal comprising a memory and a processor, the memory storing computer readable instructions, the computer readable instructions being executed by the processor such that the processor performs the following steps:

    Reporting the user identifier and the corresponding user scenario information to the server, so that the server queries the user cluster to which the reported user identifier belongs, and obtains the cluster general service recommendation mode corresponding to the user cluster, where the user scenario information meets the cluster common When the triggering condition in the service recommendation mode is used, the service information corresponding to the met trigger condition in the cluster general service recommendation mode is recommended; the user cluster according to the individual service recommendation manner in the personal service recommendation mode set of the multi-user source Corresponding user identifiers are obtained by clustering; the cluster general service recommendation manner is generated according to the personal service recommendation manner corresponding to the user cluster in the set of personal service recommendation manners;

    Receiving the service information recommended by the server;

    Displaying a notification interface, and displaying a corresponding service portal in the notification interface according to the service information.
19. The terminal according to claim 18, wherein the reporting the user identifier and the corresponding user scenario information to the server, so that the server queries the user cluster to which the reported user identifier belongs, and obtains the cluster common to the user cluster. In the service recommendation mode, when the user scenario information satisfies the trigger condition in the cluster general service recommendation mode, the cluster general service is recommended. The service information corresponding to the met trigger condition in the recommendation mode includes:

    Reporting the user identifier and the corresponding user scenario information to the server, so that the server recommends the personal service recommendation manner when the user scenario information meets a trigger condition in the personal service recommendation manner corresponding to the reported user identifier The service information corresponding to the met trigger condition; when the user scenario information does not meet the trigger condition in the personal service recommendation manner corresponding to the reported user identifier, querying the user cluster to which the reported user identifier belongs, acquiring the The cluster general service recommendation mode corresponding to the user cluster, when the user scenario information satisfies the trigger condition in the cluster general service recommendation mode, the service information corresponding to the met trigger condition in the cluster general service recommendation mode is recommended.
20. The terminal according to claim 18, wherein the recommended service information is included in a cluster general service recommendation mode selected according to the weights corresponding to the acquired cluster general service recommendation manners; the computer readable instructions further The processor performs the following steps:

    Displaying a service cancellation control in the notification interface according to the service information;

    Entering an application pointed to by the service portal when a user operation instruction for the service portal is detected;

    Sending user feedback to the server when detecting a user operation instruction for the service portal or the service cancellation control, so that the server adjusts the recommended cluster general service where the service information is recommended according to the user feedback The weight corresponding to the recommended method.
21. A non-transitory computer readable storage medium storing computer readable instructions, the computer readable instructions being executed by a processor, causing the processor to perform the method of any one of claims 1 to 10. The steps of the method.

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