Personalized information recommendation method by information fusion

Abstract

The invention relates to a personalized information recommendation method by information fusion, belonging to the technical field of Internet information recommendation. The method includes first pre-processing a data set to extract item shape information: determining a relationship type between items, constructing a relationship network between items, determining item text information, and determining item image information; using a network representation learning method to extract network relationship features, extracting text features by using a text representation learning method, and extracting image features by using an image feature extraction method; then calculating a user's preference feature value for each item in each dimension; finally inputting preference features into a sorting model, and recommending items with scores TOP-N in an alternative set to the user. Compared with the prior art, the method improves the accuracy of recommendation results by excavating and utilizing attribute information of the items to supplement sparse user active interaction data; and the integration of the item attribute information can make the recommendation not only rely on rating data,but also help solve the problem of cold boot of new items.

Description

technical field [0001] The invention relates to an information recommendation method in the Internet field, in particular to an information fusion personalized recommendation method, which belongs to the technical field of Internet information recommendation. Background technique [0002] With the development of information technology and the Internet, the current society has gradually changed from an era of information scarcity and slow communication to an era of information overload and information redundancy. For the information receiver, it is impossible to quickly find the target information from the massive information; for the information producer, it is impossible to expose the information to the target users. The recommendation system emerged as a bridge between the two. The effect of the recommendation system depends on the performance of the recommendation algorithm, and the research on the recommendation algorithm in the academic circle has never stopped. [00...

AI Technical Summary

Problems solved by technology

[0005] In order to solve the cold start problem of new items in existing recommendation methods and optimize the accuracy of recommendation results, the present invention proposes an information fusion personalized recommendation method, which optimizes the recommendation effect by exploring and utilizing the value of item information to supplement user interaction information

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