Project recommendation method and device

Abstract

The invention provides a project recommendation method and device. According to recorded grading objects and scores thereof to projects, the score mean value of the grading objects to the projects and the types of all projects are determined firstly; then the score mean value of the grading objects to the project types is counted; first related objects with similar type preferences are determined from target objects; then second related objects with similar project preferences are found out from the first related objects; the eligible projects are extracted from the projects which are not graded by the target objects and recommended to the target objects. According to the embodiment of the invention, users with related preferred projects and types are selected out and invalid information not interested by the users are removed by using the interest degrees of the users to different types of projects; all effective information is used when the similarity among the users is calculated, so that the similarity calculation is more accurate, the accuracy of calculating the similarity among the users can be effectively enhanced, and the recommendation quality of a recommendation system is effectively improved.

Description

technical field [0001] The present invention relates to the field of network technology, in particular to an item recommendation method and an item recommendation device. Background technique [0002] With the rapid development of emerging services such as cloud computing, the Internet of Things, and social networks, the era of big data has arrived, and the amount of data information in various fields has exploded, leading to so-called "information flooding" and "information wandering". A large amount of intricate data information makes users feel lost and confused when looking for interesting information. At the same time, this is both an opportunity and a challenge for enterprises. How to obtain and master useful information is the cornerstone for enterprises to maintain their competitive advantages. [0003] Personalized recommendation is one of the most effective tools to solve the problem of information overload. Among them, collaborative filtering algorithm is conside...

AI Technical Summary

Problems solved by technology

[0005] The problem in the above background technology is: in the actual recommendation system, the user may only rate some or even one item, and most users in the nearest neighbors of the target user do not rate the target item, although the similarity is high, However, there are large accidental factors in such similarity calculation results, and accurate prediction results cannot be obtained.

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