计算机工程 ›› 2018, Vol. 44 ›› Issue (5): 140-145.doi: 10.19678/j.issn.1000-3428.0046782

• 人工智能及识别技术 • 上一篇    下一篇

基于情境感知的广播电视群组发现策略

陈建,王子磊,奚宏生   

  1. 中国科学技术大学 自动化系,合肥 230027
  • 收稿日期:2017-04-14 出版日期:2018-05-15 发布日期:2018-05-15
  • 作者简介:陈建(1992—),男,硕士研究生,主研方向为推荐系统;王子磊,副教授;奚宏生,教授。
  • 基金项目:
    国家自然科学基金(61233003,61673362);中央高校基本科研业务费和中国科学院青年创新促进会联合基金。

TV Group Detection Strategy Based on Context Awareness

CHEN Jian,WANG Zilei,XI Hongsheng   

  1. Department of Automation,University of Science and Technology of China,Hefei 230027,China
  • Received:2017-04-14 Online:2018-05-15 Published:2018-05-15

摘要: 为解决广播用户收视兴趣复合性问题,提出一种基于时间情境感知的电视用户群组发现策略。采用张量分解获取节目和收视时间的隐性特征矩阵,利用马尔可夫聚类算法实现对记录的分类,并根据记录分类结果发现用户群组,用户组群以家庭用户为单位,识别出特定时段具有相似观看兴趣的所有家庭用户,并针对家庭用户群组实现节目推荐功能。实验结果表明,该策略可减小组内用户与群组整体在观看兴趣方面的平均绝对误差,并提高组内成员的观看兴趣相似度。

关键词: 推荐系统, 协同过滤, 情境感知, 张量分解, 马尔可夫聚类算法

Abstract: In order to solve the compounding problem of broadcast audience viewing interest,this paper proposes a TV group detection strategy based on context awareness.Using tensor decomposition to obtain the hidden feature matrix of programs and viewing time,using Markov clustering algorithm to achieve the classification of records,and find the user group according to the record classification results.The user group identifies the specific user as the unit of home users.All home users have similar viewing interests during the time period,and implement program recommendation functions for home user groups.Experimental results show that the strategy reduces the average absolute error in the viewing interests of users and groups within the group,and improves the similarity of viewing interests among members of the group.

Key words: recommender system, collaborative filtering, context awareness, tensor decomposition, Markov clustering algorithm

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