System, method and game platform capable of recommending games in personalization mode

A recommendation system and game technology, applied in the Internet field, can solve problems such as low recommendation accuracy, uniform recommended content, and recommendation algorithms that do not have machine learning capabilities, so as to improve the recommendation accuracy and broaden the scope of the game.

Active Publication Date: 2013-06-05
SHENZHEN TIANQU NETWORK SCI & TECH CO LTD
View PDF2 Cites 49 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Existing game platforms generally list the games provided by game service providers according to the classification of games (such as card games, competitive games, etc.). This unified recommendation method has the following disadvantages: the recommended content is stereotyped and cannot be true. Touch and predict the user's game preferences; the recommendation algorithm used does not have machine learning capabilities, users cannot give feedback on the recommendation results, the recommendation results cannot evolve, and the recommendation accuracy is not high

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • System, method and game platform capable of recommending games in personalization mode
  • System, method and game platform capable of recommending games in personalization mode
  • System, method and game platform capable of recommending games in personalization mode

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0023] If the user has already logged in to the platform through the ID of the user's login game platform, that is, this embodiment is aimed at users who have a history of using the game platform, such as figure 2 As shown, the recommended method includes the following steps:

[0024] Step S201, collecting the user's historical interest data, and analyzing according to the historical interest data to obtain a ranking list of the user's preference for games, the list includes "favorite game list";

[0025] The recommendation system collects the historical interest data of all users and the game history data of all games, and then classifies the historical interest data of all users according to the user identifier to obtain the historical interest data of each user, and classifies the historical interest data of all games according to the game identifier. Classify the game history data of each game to obtain the game history data of each game. For the user corresponding to the...

Embodiment 2

[0041] If the user has already logged in to the platform through the ID of the user's login game platform, that is, this embodiment is aimed at users who have a history of using the game platform, such as image 3 As shown, the recommended method includes the following steps:

[0042] Step S301, collect historical interest data of users, analyze according to the historical interest data, and obtain a ranking list of users' preference for games, the list includes "favorite game list" and "dislike game list";

[0043] For the "favorite game list", its obtaining process is the same as the process of obtaining the "favorite game list" in step S201 of the first embodiment;

[0044] As for the "disliked game list", the obtaining process is similar to the process of obtaining the "favorite game list" in step S201 of the first embodiment. Here, a game with a low rating is regarded as a game that the user does not like. Similarly, calculate the behavior values ​​of each dimension for...

Embodiment 3

[0051] If the user has already logged in to the platform through the ID of the user's login game platform, that is, this embodiment is aimed at users who have a history of using the game platform, such as Figure 4 As shown, the recommended method includes the following steps:

[0052] Step S401, collect the historical interest data of the user and his friends, and analyze the user's own historical interest data to obtain a ranking list of the user's own preference for games, which includes "favorite game list" and "dislike game list". "; according to the analysis of the historical interest data of the friends, a ranking list of the friends' liking for the game is obtained, and the list includes "a list of games liked by the friends". The friends mentioned here are the friends of the user on the game platform or the people who follow on the game platform.

[0053] For the "favorite game list" and "dislike game list", the obtaining process is the same as step S301 of the secon...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention discloses a system, a method and a game platform capable of recommending games in a personalization mode. The recommending system recommends the games according to a user identifier, and comprises a behavioral analysis module, a relative detecting module and a recommending module, wherein the behavioral analysis module is used for collecting historical data in which a user is interested and historical data about different games with which the user plays, obtaining basic preferring value of the user to different games according to the collected data, and obtaining a game preferring degree ranking list of the user to different games. The relative detecting module is used for calculating relevancy degrees of different games in the game preferring degree ranking list according to a relevancy algorithm, and ranking the relevancy degrees to obtain a possibly preferable degree ranking list of the games. The recommending module is used for recommending the possibly preferable degree ranking list of the games to the user. The recommending system analyzes the collected historical data in which the user is interested and the historical data of different games, explores the favor degree of the user to the games, and therefore the recommending system can specifically recommend the games to the users with different personalities.

Description

technical field [0001] The present invention relates to the technical field of the Internet, in particular to a system and method for personalized game recommendation and a game platform. Background technique [0002] With the development of Internet technology, online games have become a network service that more and more Internet users pay attention to. Existing game platforms generally list the games provided by game service providers according to the classification of games (such as card games, competitive games, etc.). This unified recommendation method has the following disadvantages: the recommended content is stereotyped and cannot be true. Touch and predict the user's game preferences; the recommendation algorithm adopted does not have machine learning capabilities, the user cannot give feedback on the recommendation results, the recommendation results cannot evolve, and the recommendation accuracy is not high. Therefore, it is necessary to provide a system or meth...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
Patent Type & Authority Applications(China)
IPC IPC(8): G06F19/00
Inventor 向灿马志勇杨庆昌
Owner SHENZHEN TIANQU NETWORK SCI & TECH CO LTD
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap