Real time streaming-oriented television program recommendation system

Abstract

The invention discloses a real time streaming-oriented television program recommendation system. The real time streaming-oriented television program recommendation system comprises a user information collecting module, a program model definition module, a user preference tracking module, a program recommendation module and a recommendation result display module, wherein the user information collecting module is used for automatically and transparently collecting user watching information when users watch television programs; the program model definition module is used for extracting program related information from internet and establishing a program model by adopting an information extraction technology; the user preference tracking module is for generating a user preference model by using the user watching information collected by the user information collecting module and the program model established by the program model definition module; the program recommendation module is used for generating recommendation results by using extended Jaccard similarity according to the current user preference; and the recommendation result display module is used for adding art designing and animation effects to the recommendation results on the basis of text recommendation results generated by the program recommendation module. The real time streaming-oriented television program recommended system has the advantages of having stronger individuation, keeping in step with the preference of the user to change, solving the problem that the traditional system asks for the clear feedback of users, adding time maintenance for programs and carrying out pertinence recommendation.

Description

technical field [0001] The invention relates to a system in the field of computer application technology, in particular to a real-time stream-oriented television program recommendation system. Background technique [0002] Recommender systems have been a very important and active research area since the middle of the 20th century. Since the recommendation system involves a wide range of academic fields, including information retrieval, product classification, behavior modeling, real-time recommendation, and it can perform personalized recommendations, the research enthusiasm for it has been enduring. The main functions of the recommendation system are: tracking user behavior and screening appropriate content. In this way, users are freed from the burden of blindly searching in massive data, and directly provide the content that users are most likely to prefer. Today, recommendation systems have penetrated into all aspects of commercial marketing, mainstream applications su...

AI Technical Summary

Problems solved by technology

[0004] Although the recommendation system has achieved great results and has been accepted and even relied on by the majority of users, in terms of TV program recommendation, a complete set of TV program recommendation system with high accuracy and wide coverage has not yet appeared on the market.

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