Search

CN-122019867-A - Dynamic recommendation and rule configuration method and system for vehicle-mounted scene community

CN122019867ACN 122019867 ACN122019867 ACN 122019867ACN-122019867-A

Abstract

The invention provides a method and a system for dynamically recommending and configuring rules of a vehicle-mounted scene community, which belong to the technical field of vehicle-mounted software, wherein the method comprises the steps of acquiring dynamic target scene rules from the vehicle-mounted scene community; when the preference information of the target user is obtained, the labels of the scene data are combined with the preference information of the target user to screen out scenes recommended to the target user from the scene data. According to the method and the device, the matching degree of the recommended scene and the user requirement is greatly improved through the custom rule and the tag matching, and the time for the user to acquire the effective scene is greatly shortened. The method can adjust the judgment rules of the latest and popular scenes in real time according to the operation demands of the communities, adapt to operation strategies in different periods and improve the activity of the communities.

Inventors

  • XIA YUN

Assignees

  • 东风汽车集团股份有限公司

Dates

Publication Date
20260512
Application Date
20260105

Claims (10)

  1. 1. A dynamic recommendation and rule configuration method of a vehicle-mounted scene community is characterized by comprising the following steps: Acquiring a dynamic target scene rule from a vehicle-mounted scene community; acquiring a plurality of scene data, wherein each scene data is associated with at least one tag; When the preference information of the target user is obtained, according to the target scene rule, the labels of the scene data are combined with the preference information of the target user, and scenes recommended to the target user are screened out from a plurality of scene data.
  2. 2. The method of claim 1, wherein the step of obtaining dynamic target scene rules from the vehicle scene community comprises: Setting target scene rules, wherein the target scene rules comprise latest scene rules and/or hot scene rules; Receiving a latest scene rule editing request, wherein the latest scene rule comprises at least one of release on the near X days and latest Y pieces; receiving X, Y a setting request; receiving a hot scene rule editing request, wherein the hot scene rule comprises Z pieces before downloading; A setting request for Z is received.
  3. 3. The method according to claim 1 or 2, wherein the step of obtaining a plurality of scene data, each scene data being associated with at least one tag comprises: Receiving a scene classification editing request to obtain scene classification; Receiving a label editing request and distributing at least one label for each scene category; and receiving a scene editing request, and distributing scene categories and labels for the first target scene.
  4. 4. The method according to claim 3, wherein when the preference information of the target user is acquired, the step of selecting the scene recommended to the target user from the plurality of scene data in combination with the preference information of the target user according to the target scene rule includes: According to the target scene rule, a scene conforming to the target scene rule is screened from a plurality of scene data; And matching the labels of the scenes conforming to the target scene rule with preference information of the target user, and screening out scenes with matching degree exceeding a preset threshold as scenes recommended to the target user.
  5. 5. A method according to claim 3, wherein said obtaining a plurality of scene data, each scene data associated with at least one tag step, comprises, after: When the historical behaviors of the target user are obtained, a scene conforming to the target scene rule is screened from a plurality of scene data according to the target scene rule; Obtaining similar users of the target user by adopting a collaborative filtering algorithm according to the historical behaviors of the target user; and taking the scene which is the same as the scene liked by the similar user in the scenes conforming to the target scene rule as the scene recommended to the target user.
  6. 6. The method of claim 3, wherein the step of obtaining a plurality of scene data, each scene data associated with at least one tag further comprises: Receiving a scene visibility editing request, and setting the first target scene visibility to be based on the train range of the target user vehicle according to the train information of the target user vehicle; when the preference information of the target user is obtained, according to the target scene rule, the step of selecting the scene recommended to the target user from the plurality of scene data by combining the preference information of the target user comprises the following steps: According to the target scene rule, a scene conforming to the target scene rule is screened from a plurality of scene data; matching the labels of the scenes conforming to the target scene rule with preference information of a target user, and screening out scenes with matching degree exceeding a preset threshold; And excluding scenes which do not belong to the same vehicle system as the target user from the scenes with the matching degree exceeding a preset threshold by combining the vehicle system information of the target user, so as to obtain scenes recommended to the target user.
  7. 7. The method as recited in claim 1, further comprising: Receiving a sharing request, and sharing the second target scene to the community; the visibility of the second target scene is set to be based on the train range, so that only the sharing scene can be checked by the same train user.
  8. 8. A dynamic recommendation and rule configuration system for a vehicular scene community, configured to enable the method of any one of claims 1 to 7, the system comprising: The rule configuration module is used for acquiring dynamic target scene rules from the vehicle-mounted scene community; The classification management module is used for acquiring a plurality of scene data, and each scene data is associated with at least one tag; And the recommendation module is used for screening scenes recommended to the target user from a plurality of scene data according to the labels of the scene data and the preference information of the target user when the preference information of the target user is acquired.
  9. 9. An electronic device, comprising: one or more processors; A memory for storing one or more programs; when executed by the one or more processors, causes the one or more processors to implement the method of any of claims 1 to 7.
  10. 10. A computer readable medium having a computer program stored thereon, characterized in that the computer program, when executed by a processor, implements the steps of the method according to any of claims 1 to 7.

Description

Dynamic recommendation and rule configuration method and system for vehicle-mounted scene community Technical Field The invention relates to the technical field of vehicle-mounted software, in particular to a method and a system for dynamic recommendation and rule configuration of a vehicle-mounted scene community. Background With the development of intelligent internet-connected automobiles, vehicle-mounted scene application gradually becomes an important component for improving user experience. The user can acquire, share and use various scenes through the vehicle-mounted scene community, such as a holiday scene, an intelligent driving scene, an entertainment scene and the like. However, the existing in-vehicle scene communities have the following problems: The recommendation accuracy is insufficient, in the prior art, fixed recommendation rules are mostly adopted, dynamic adjustment cannot be carried out according to user preference and scene characteristics, so that the matching degree of recommended scenes and user requirements is low, and the efficiency of acquiring effective scenes by users is low. The rule configuration flexibility is poor, namely the judging rules of the popular scene and the latest scene are usually fixed in the system, an administrator cannot customize the rules according to community operation requirements, and community operation strategies in different periods are difficult to adapt. The scene classification system is imperfect, and the lack of uniform scene classification standards and the confusion of scene labels lead to the difficulty of users in finding required scenes quickly and influence the accuracy of recommendation. The sharing mechanism is limited in that user-defined scenes shared by users lack effective visibility control, different train users can see unsuitable scenes, user experience is affected, and user participation is low. Disclosure of Invention The invention aims to solve the problems of insufficient recommendation accuracy, inflexible rule configuration, imperfect classification system, limited sharing mechanism and the like in the existing vehicle-mounted scene communities, and provides an improved technical scheme based on dynamic recommendation and rule configuration of the vehicle-mounted scene communities. In a first aspect, an embodiment of the present invention provides a method for dynamically recommending and configuring rules of a vehicle-mounted scene community, including: Acquiring a dynamic target scene rule from a vehicle-mounted scene community; acquiring a plurality of scene data, wherein each scene data is associated with at least one tag; When the preference information of the target user is obtained, according to the target scene rule, the labels of the scene data are combined with the preference information of the target user, and scenes recommended to the target user are screened out from a plurality of scene data. In a preferred embodiment, the step of acquiring dynamic target scene rules from the vehicle scene community includes: Setting target scene rules, wherein the target scene rules comprise latest scene rules and/or hot scene rules; Receiving a latest scene rule editing request, wherein the latest scene rule comprises at least one of release on the near X days and latest Y pieces; receiving X, Y a setting request; Receiving a hot scene rule editing request, wherein the hot scene rule comprises Z pieces before downloading; A setting request for Z is received. In a preferred embodiment, the step of obtaining a plurality of scene data, each scene data being associated with at least one tag comprises: Receiving a scene classification editing request to obtain scene classification; Receiving a label editing request and distributing at least one label for each scene category; and receiving a scene editing request, and distributing scene categories and labels for the first target scene. In a preferred embodiment, when the preference information of the target user is obtained, according to the target scene rule, the step of selecting, by combining the preference information of the target user and the tag of the scene data, the scene recommended to the target user from the plurality of scene data includes: According to the target scene rule, a scene conforming to the target scene rule is screened from a plurality of scene data; And matching the labels of the scenes conforming to the target scene rule with preference information of the target user, and screening out scenes with matching degree exceeding a preset threshold as scenes recommended to the target user. In a preferred embodiment, the step of obtaining a plurality of scene data, each scene data being associated with at least one tag, comprises: When the historical behaviors of the target user are obtained, a scene conforming to the target scene rule is screened from a plurality of scene data according to the target scene rule; Obtaining similar users of the target user by ado