Collaborative filtering recommendation approach for dealing with ultra-mass users

Abstract

The invention is a kind of synergistic filter recommending method for processing super-large user quantity, which belongs to network technology field. The method is: the point data of the project by the user are memorized in distributed way, namely that each user stores the point data of itself project, and acquires the point data of similar user through the distributed hash table, and acquires the predicted value through the synergistic filter method, then acquires the recommended value further, and restrains the quantity of similar user returned from the network covered by the hash table of each project, and adjusts the affection of each user, makes the affection of user which has more similar number and point two-tuples is larger, thus it upgrades the accuracy of prediction. The invention introduces the hash table route algorithm into the synergistic filter system, and it is improved, it solves the problem that the extensible ability of current filter system is bad and it upgrades the recommendation quality.

Description

technical field [0001] The invention relates to a collaborative filtering recommendation method, in particular to a collaborative filtering recommendation method for processing a large number of users, and belongs to the field of network technology. Background technique [0002] The exponential expansion of information resources on the Internet has brought the so-called "information overload" and "information obsession" problems, that is, it is difficult for people to find the information they are interested in, and even if they find some, it is often mixed with a lot of "noise". Therefore, technologies such as Internet-oriented information retrieval, information filtering and collaborative filtering have emerged. However, information retrieval is not intelligent and cannot learn the interests of users, especially for users with specific professional interests, inputting the same keywords can only get the same retrieval results. Information filtering cannot distinguish the ...

AI Technical Summary

Problems solved by technology

[0004] The purpose of the present invention is to provide a collaborative filtering recommendation method for dealing with a large number of users in view of the defects or deficiencies in the prior art, so as to solve the problem when the traditional centralized user-based collaborative filtering recommendation method encounters a large number of users

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