作 者: ();
机构地区: 广东海洋大学
出 处: 《统计学与应用》 2019年第4期522-530,共9页
摘 要: 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。 In order to integrate and utilizeexisting data better,and improve the marketing effectiveness of TV programproducts,this paper processes the data of the watching information of TV usersand establishes the user preference model to obtain three preference types ofeach user,and then uses the collaborative filtering algorithm to carry outpersonalized recommendation of individual users.In addition,we use K-meansalgorithm as well as the KNN algorithm to divide the users into groups andobtain the recommendation of each user group,thereby effectively solving theproblem of personalized recommendation ofthe users.
领 域: []