Accurate recommendation system and method based on parallel processing of collaborative filtering and association rules

Abstract

The invention relates to data processing and recommendation in computer techniques, discloses an accurate recommendation system and method based on parallel processing of collaborative filtering and association rules, solves the problem that a recommendation system cannot be applicable to recommendation of industries with large and complicated index systems such as a movie in traditional technique and achieves accurate recommendation. The recommendation method includes the steps: a, data preprocessing stage: acquiring film index attribute information and user characteristic index information, preprocessing the acquired film index attribute information and the acquired user characteristic index information, and taking the preprocessed film index attribute information and the preprocessed user characteristic index information as basic data of prediction and recommendation; b, prediction and recommendation stage: calculating film index attributes based on the association rules, generating specific film groups according to target users, calculating user characteristic indexes based on collaborative filtering rules, finding out similar user groups, recommending special films to the target users with same hobby orientations, and predicting future user groups; c, evaluation stage: evaluating accuracy of prediction results. The recommendation method is applicable to recommendation of specific films to the target users in movie industries.

Description

technical field [0001] The invention relates to data processing and recommendation in computer technology, in particular to an accurate recommendation system and method based on collaborative filtering and parallel processing of association rules. Background technique [0002] With the rapid development of network technology, information technology and computer technology, as early as 2010, the world entered the era of big data. How to accurately discover users' purchasing preferences and recommend them is a hot research issue at present. [0003] However, unlike ordinary retail products, movies involve multiple index systems, and users have different interest orientations and tastes. Therefore, a traditional single recommendation system cannot fully achieve the purpose of accurate recommendation. SUMMARY OF THE INVENTION [0004] The technical problem to be solved by the present invention is: to propose a precise recommendation system and method based on collaborative fi...

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Problems solved by technology

[0004] The technical problem to be solved by the present invention is to propose an accurate recommendation system and method based on collaborative filtering and association rules parallel processing, so as to solve the problem that the recommendation system in the traditional technology cannot adapt to the recommendation of an industry with a huge and cumbersome index system such as movies. problem, to achieve accurate recommendation

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