Three-dimensional time sequence dynamic model based mobile phone game recommendation system

A dynamic model and mobile game technology, applied in special data processing applications, instruments, electrical digital data processing, etc., can solve the problems of high loss rate of game users, increase of enterprise promotion costs, user troubles, etc.

Active Publication Date: 2016-08-31
SOUTH CHINA UNIV OF TECH
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Blind recommendation results will bring troubles to users and increase the promotion costs of ent

Method used

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  • Three-dimensional time sequence dynamic model based mobile phone game recommendation system
  • Three-dimensional time sequence dynamic model based mobile phone game recommendation system
  • Three-dimensional time sequence dynamic model based mobile phone game recommendation system

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Embodiment Construction

[0047] The present invention will be further described below in conjunction with specific embodiments.

[0048] Such as figure 1 As shown, the mobile phone game recommendation system based on a three-dimensional time-series dynamic model in this embodiment includes a user behavior data acquisition module, a game information acquisition module, a user behavior analysis module, a game tag module, a time-series dynamic model module, and a game recommendation module. The user behavior data acquisition module obtains user behavior logs from the relevant game operation platform; the game information acquisition module crawls the game profile information and data preprocessing on the official website of the corresponding mobile game recommendation platform; After importing the user behavior log, the user behavior analysis module performs data analysis and data vectorization on the log to form the user's feature vector; the game tag module uses the relevant game content profile to mark t...

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Abstract

The invention discloses a three-dimensional time sequence dynamic model based mobile phone game recommendation system. The system comprises a user behavior data acquisition module, a game information acquisition module, a user behavior analysis module, a game label module, a time sequence dynamic model module and a game recommendation module. According to the system, a dynamic user behavior is analyzed according to acquired user behavior data and the interest changes of new and old users are tracked; when the user interests are changed or possibly run away, games with relatively high similarity with user interested games and the game popularity are comprehensively considered and optimal recommendation results are given to the users; in combination with the timeliness of the games and the users, a time window based user activeness score computing method is established; and game labels are introduced for performing corresponding mapping on the users, so that the diversity of game recommendation is enriched, the users can feel game recommendation with continuous new element changes, and the novelty of game recommendation is enhanced.

Description

Technical field [0001] The invention relates to the technical field of product recommendation, in particular to a mobile phone game recommendation system based on a three-dimensional time series dynamic model. Background technique [0002] With the advent of the era of big data and the growing popularity of mobile games, mobile game users have exploded. Game operating platforms generally directly recommend popular games to users, and do not make full use of user information to make targeted personalized recommendations. Blind recommendation results will cause confusion to users and increase the promotion costs of enterprises, which makes the current game operating platform game user churn rate high. The competition of mobile game operating platforms is fierce. How to attract new users and continue to retain old users on the platform is the core issue of the game operating platform. Therefore, it is of great significance to analyze user behavior in combination with big data, cap...

Claims

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Application Information

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IPC IPC(8): G06F17/30
CPCG06F16/9535
Inventor 董守斌王进董守玲胡金龙张晶
Owner SOUTH CHINA UNIV OF TECH
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