Collaborative filtering method and system based on similarity propagation

A similarity transfer and collaborative filtering technology, applied in the field of collaborative filtering based on similarity transfer, can solve the problems of low similarity accuracy and recognition, and unsatisfactory recommendation success rate, so as to improve the recognition and recommendation coverage. High, avoids the effect of similarity measures
CN103309967AActive Publication Date: 2013-09-18TSINGHUA UNIV
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
TSINGHUA UNIV
Publication Date
2013-09-18

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Abstract

The invention relates to the technical field of recommendation, in particular to a collaborative filtering method and system based on similarity propagation. The method comprises the steps as follows: traversing historical behavior data of all users to obtain a relationship vector describing the preferences of all the users on articles; setting a threshold value by the relationship vector and calculating the similarities among the users; calculating the similarity between a target user and the other user, with a similarity value of zero in the matrix, by a similarity propagation calculation principle; obtaining an estimation value of the preference degree of a current user on an unselected article according to the preference degree of the other user most similar to the target user on an article unselected by the target user; and screening the prediction results of all the users to generate recommended articles for all the users. The system comprises a data relationship vector module, a threshold value judgment module, a similarity propagation calculation module, a preference degree estimation module and a prediction screening module.
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Description

technical field

[0001] The invention relates to the technical field of network recommendation, in particular to a collaborative filtering method based on similarity transfer. Background technique

[0002] The development of information technology and the Internet has brought people from the era of information scarcity to the era of information overload. In this era, it is difficult for information consumers to find what they are really interested in from a large amount of information, and it is also difficult for information producers to make the information they produce stand out and match suitable users. As one of the very potential information filtering technologies in the 21st century, the recommendation system can better solve this contradiction. It analyzes the user's historical behavior, establishes the user's interest model, and finally connects the user with the information. On the one hand, it helps the user to discover the information that is valuable to him, and...

Claims

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