%0 Journal Article
%T 基于修正Tanimoto系数的电视节目个性化推荐方法研究<br>Research on Personalized Recommendation Method of TV Programs Based on Modified Tanimoto Coefficient
%A 王子涛
%A 伍发珍
%A 江铭海
%A 董云薪
%A 林耿
%J Hans Journal of Data Mining
%P 181-186
%@ 2163-1468
%D 2021
%I Hans Publishing
%R 10.12677/HJDM.2021.113016
%X 随着互联网产业的发展，电视节目的个性化推荐已经成为了许多电视节目制作者和观众们的共同需求。为达到电视节目个性化推荐的目的，本文通过结合用户共同评分项和用户所有评分项之间的关系，将基于修正Tanimoto系数的推荐算法运用于电视节目个性化推荐的研究中。实验结果表明，本文所运用的算法具有一定的提高电视节目个性化推荐系统的精度的效果。<br />
With the development of the Internet industry, the individualization of TV programs has become the common demand of many TV program makers and viewers. In order to achieve the purpose of personalized recommendation of TV programs, this paper combined the relationship between user common rating items and user all rating items, and applied the collaborative filtering recommen-dation algorithm modified Tanimoto coefficient to improve similarity measure in the research of personalized recommendation of TV programs. Experimental results show that the algorithm used in this paper can improve the accuracy of TV program personalized recommendation system to a certain extent.
%K Tanimoto系数，相似度，协同过滤算法，电视节目推荐<br>Tanimoto Coefficient
%K Similarity
%K Collaborative Filtering Algorithm
%K TV Program Recommendation
%U http://www.hanspub.org/journal/PaperInformation.aspx?PaperID=43666