The Personalized Tagging Recommendation System Based On the Question-Answering System by Behavioral Analysis

摘要：

Collaborative tagging system has become more and more popular and recently achieved widespread success due to flexibility and conceptual comprehensibility of tagging systems. Recommendation system has the access to adopt tagging systems to achieve better performance. With the development of the QuestionAnswering System, we can chat with it. The QuestionAnswering Systems are more widely used in Intelligent Service field. However, Recently the recommender system mostly make the user pattern by analyzing the behavior of Internet users rather than analyzing dialogues between a user and Robot in real time. In this paper, we use tags to make user interest model based on dialogues between users and QuestionAnswering System by extracting the users feature information, and propose a new method to compute the weight of tags. Also we put forward a hybrid recommendation strategy based on the collaborative filtering and content-based recommendation.

关键词： Tagging System Behavioral Analysis Text Mining Recommendation System

作者: Huijing Cao Junzhong Gu Yan Yang

作者单位: Department of Computer Science and Technology East China Normal University Shanghai,200241, China

会议类型: 国际会议

会议名称: 2010 International Conference on Circuit and Signal Processing(2010年电路与信号处理国际会议 ICCSP 2010)

会议地点: 上海

会议语种:英文

页码: 265-269

在线出版日期: 2010-12-25（万方平台首次上网日期，不代表论文的发表时间）