%0 Journal Article
%T 基于协同过滤算法的电视用户个性化推荐<br> Personalized Recommendation of TV Users Based on Collaborative Filtering Algorithm
%A 陈星星
%A 李瑞涛
%A 廖军华
%A 吴延科
%J Statistics and Applications
%P 522-530
%@ 2325-226X
%D 2019
%I Hans Publishing
%R 10.12677/SA.2019.84071
%X <span style=\"font-size:14px;\">为了更好地整合和利用现有的数据，提高电视节目产品营销效益，本文通过对广电网络公司电视用户的收看信息数据进行数据处理，建立用户偏好模型，得到各个用户的三个偏好类型，然后使用协同过滤算法进行单个用户的个性化推荐，以及使用K-means算法和KNN算法将用户进行分群，得到用户群的推荐，进而有效地解决了用户个性化推荐的问题。<br />
In order to integrate and utilize
existing data better, and improve the marketing effectiveness of TV program
products, this paper processes the data of the watching information of TV users
and establishes the user preference model to obtain three preference types of
each user, and then uses the collaborative filtering algorithm to carry out
personalized recommendation of individual users. In addition, we use K-means
algorithm as well as the KNN algorithm to divide the users into groups and
obtain the recommendation of each user group, thereby effectively solving the
problem of personalized recommendation of
the users.</span>
%K K-means聚类分析，KNN算法，协同过滤，个性化推荐<br> K-means
%K KNN
%K Collaborative Filtering
%K Personalized Recommendation
%U http://www.hanspub.org/journal/PaperInformation.aspx?PaperID=31659