CN-116821517-B - Virtual room recommendation method and device, storage medium and computer equipment

CN116821517BCN 116821517 BCN116821517 BCN 116821517BCN-116821517-B

Abstract

According to the virtual room recommending method, the device, the storage medium and the computer equipment, when the fact that a first user refreshes a virtual room recommending page is monitored, at least one second user which has interaction behaviors with the first user but does not pay attention to each other in a historical period can be firstly obtained to form a second user set, then the second user in a virtual room is screened out from the second user set to form a recommending user set, at least one target recommending user can be determined from the recommending user set based on the interaction behaviors between each second user in the recommending user set and the first user, finally room identification of a virtual room where each target recommending user is located can be obtained, the virtual room recommending page is updated by utilizing each room identification, so that the first user can reunite with the target recommending user which is online at the same time and interact with the target recommending user, communication and understanding are promoted, and a relation chain between the two users is pulled up, and therefore user experience is improved.

Inventors

LI LIJIA
XIAO YAN
ZHOU TAO
WANG ZHENG
LI DAN
CAI BIN
LI YEHUA
XU ZHIJIAN
XIE RUI

Assignees

广州趣研网络科技有限公司

Dates

Publication Date: 20260505
Application Date: 20230424

Claims (9)

1. A method of virtual room recommendation, the method comprising: When a first user refreshing virtual room recommendation page is monitored, a second user set corresponding to the first user is obtained, wherein the second user set comprises at least one second user which has interaction behaviors with the first user but does not pay attention to each other in a historical period; Screening a second user currently in the virtual room from the second user set to form a recommended user set; determining at least one target recommended user from the recommended user set based on interaction behavior between each second user in the recommended user set and the first user; acquiring room identifiers of virtual rooms in which each target recommended user is located, and updating the virtual room recommendation page by utilizing each room identifier; When the first user and other users are monitored to generate interaction behaviors, judging whether the other users are second users in the second user set or not; If yes, updating the interaction behaviors of the other users and the first user; If not, the other users are added to the second user set under the condition that the other users do not pay attention to the first user.
2. The method of claim 1, wherein the screening the second user from the second set of users for a second user currently in the virtual room to form the set of recommended users comprises: And acquiring online second users in the second user set, and screening the second users currently in the virtual room from the online second users to form a recommended user set.
3. The virtual room recommendation method of claim 1, wherein the determining at least one target recommended user from the set of recommended users based on the interaction behavior between each second user of the set of recommended users and the first user comprises: determining an interaction score corresponding to each second user according to the interaction behavior between each second user and the first user in the recommended user set; at least one target recommended user is determined from the set of recommended users based on each interaction score.
4. A virtual room recommendation method as claimed in claim 3, wherein said determining the corresponding interaction score for each second user based on the interaction behavior between each second user in the set of recommended users and the first user comprises: extracting features of interaction behaviors of the same interaction category between each second user and the first user in the recommended user set to obtain feature values of the interaction behaviors corresponding to each second user; determining a corresponding scoring coefficient according to the interaction category; and scoring the characteristic values of each interaction behavior by using the scoring coefficients to obtain the interaction score corresponding to each second user.
5. A virtual room recommendation method as claimed in claim 3, wherein said determining at least one target recommended user from the set of recommended users based on each interaction score comprises: Ordering the interaction scores of the second users from high to low to obtain an ordering result; and screening at least one target recommended user from the recommended user set according to a preset selection rule and the sequencing result.
6. The virtual room recommendation method of claim 1, wherein the updating the virtual room recommendation page with each room identification comprises: sequencing the recommendation sequence of each room identifier according to the user behavior corresponding to each target recommended user to obtain a room sequencing list; and updating the virtual room recommendation page according to the room sorting list.
7. A virtual room recommendation device, comprising: The second user acquisition module is used for acquiring a second user set corresponding to the first user when the first user refreshing virtual room recommendation page is monitored, wherein the second user set comprises at least one second user which has interaction behaviors with the first user but does not pay attention to each other in a historical period; The second user screening module is used for screening second users currently in the virtual room from the second user set to form a recommended user set; A recommended user determining module for determining at least one target recommended user from the recommended user set based on the interaction behavior between each second user and the first user in the recommended user set; The recommendation page updating module is used for acquiring room identifiers of the virtual rooms where each target recommendation user is located and updating the virtual room recommendation page by utilizing each room identifier; the user judging module is used for judging whether the other users are second users in a second user set or not when the first user and the other users are monitored to generate interaction behaviors; The interaction behavior updating module is used for updating the interaction behaviors of the other users and the first user if yes; and the user set updating module is used for adding the other users to the second user set under the condition that the other users do not pay attention to the first user.
8. A storage medium having stored therein computer readable instructions which, when executed by one or more processors, cause the one or more processors to perform the steps of the virtual room recommendation method of any one of claims 1 to 6.
9. A computer device includes one or more processors and a memory; Stored in the memory are computer readable instructions which, when executed by the one or more processors, perform the steps of the virtual room recommendation method of any one of claims 1 to 6.

Description

Virtual room recommendation method and device, storage medium and computer equipment Technical Field The present application relates to the field of internet communications technologies, and in particular, to a virtual room recommendation method, device, storage medium, and computer apparatus. Background With the development of internet technology, social platform friend making has become a mainstream mode in modern social life, and its advantage lies in that the user can be with the other users interaction of different regional, different cultural backgrounds anytime and anywhere, after the user reaches more deep consensus with strange user after many interactions, can add the friend through the mode of paying attention to each other, easily extension social circle. In the interaction process, one-to-one interaction can be performed with the other party through private letter and other modes, or multi-person theme interaction can be performed by adding virtual rooms with different themes. After the user is online, interaction is often generated with some strange users through a mode of the virtual room and the like, however, in the related technology, the recommendation of the virtual room can only be carried out from the directions of social hotspots and interest, the recommendation direction is single, and the user can hardly expand the social circle through a mode of closing the relation chain through multiple interactions with the strange users. Disclosure of Invention The application aims to at least solve one of the technical defects, and particularly the technical defect that in the prior art, the virtual room can only be recommended from the directions of social hotspots and interests, the recommendation direction is single, and a user can hardly expand a social circle by means of multiple interaction with strangers to close the relationship chain. The application provides a virtual room recommending method, which is characterized by comprising the following steps of: When a first user refreshing virtual room recommendation page is monitored, a second user set corresponding to the first user is obtained, wherein the second user set comprises at least one second user which has interaction behaviors with the first user but does not pay attention to each other in a historical period; Screening a second user currently in the virtual room from the second user set to form a recommended user set; determining at least one target recommended user from the recommended user set based on interaction behavior between each second user in the recommended user set and the first user; And acquiring room identifiers of the virtual rooms in which each target recommended user is located, and updating the virtual room recommendation page by utilizing each room identifier. Optionally, the screening the second user from the second user set to form a recommended user set includes: And acquiring online second users in the second user set, and screening the second users currently in the virtual room from the online second users to form a recommended user set. Optionally, the determining at least one target recommended user from the recommended user set based on the interaction behavior between each second user in the recommended user set and the first user includes: determining an interaction score corresponding to each second user according to the interaction behavior between each second user and the first user in the recommended user set; at least one target recommended user is determined from the set of recommended users based on each interaction score. Optionally, the determining, according to the interaction behavior between each second user in the recommended user set and the first user, the interaction score corresponding to each second user includes: extracting features of interaction behaviors of the same interaction category between each second user and the first user in the recommended user set to obtain feature values of the interaction behaviors corresponding to each second user; determining a corresponding scoring coefficient according to the interaction category; and scoring the characteristic values of each interaction behavior by using the scoring coefficients to obtain the interaction score corresponding to each second user. Optionally, the determining at least one target recommended user from the recommended user set based on each interaction score includes: Ordering the interaction scores of the second users from high to low to obtain an ordering result; and screening at least one target recommended user from the recommended user set according to a preset selection rule and the sequencing result. Optionally, the updating the virtual room recommendation page with each room identifier includes: sequencing the recommendation sequence of each room identifier according to the user behavior corresponding to each target recommended user to obtain a room sequencing list; and updating the virtual room recommendat