System of mobile-phone application recommendation of multi-label classification and method thereof

Abstract

The invention belongs to the technical field of big data and data mining and recommendation systems, and particularly relates to a system of mobile-phone application recommendation of multi-label classification and a method thereof. The system of the invention includes five modules of a data acquisition module, a data processing module, a data storage module, a service logic module and a display module. A multi-label classification algorithm based on a random walk algorithm is provided in the invention, and multi-label data are mapped into a multi-label random walk graph. A multi-label randomwalk graph series is established when unclassified data are input; and then each node in the graph series is randomly walked to obtain probability distribution of traversing each vertex, and the probability distribution of the vertex is transformed into probability distribution of each label. According to the system and the method, a problem of user interest diversity recommendation and a problemof recommendation operation complexity increasing brought by constant user interest changes are solved, recommendation technology which is more flexible than traditional recommendation technology is obtained, and recommendation quality is improved.

Description

technical field [0001] The invention relates to the technical field of big data and data mining recommendation systems, in particular to a multi-label classification mobile phone application recommendation system and a method thereof. Background technique [0002] With the popularity of Internet users, social networks have gradually replaced our traditional information acquisition channels, such as newspapers, magazines, and TV news, and become a way for most people to receive information immediately. For example, Facebook and Twitter in foreign countries, Weibo and Renren in China. Everyone releases the information they want to express by sending messages and statuses, and spreads the information they get from others by forwarding and sharing other people's messages and statuses. This involves the issue of node influence, that is, a node that is followed by everyone can see the information published by everyone, and a node that follows everyone can see the information publ...

AI Technical Summary

Problems solved by technology

Compared with the traditional single-label classification problem, there is a significant difference in the multi-label classification problem. The relevance and co-occurrence between categories directly lead to the traditional single-label classification method cannot be directly applied to In multi-label classification problems

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