Ontology Based Service Recommendation System for Social Network

摘要：

　　The development of recommendation systems, such as traditional content-based, collaborative filtering and hybrid recommendation approaches have enabled the practical use of big data processing in WEB 3.0. In this paper, we propose an ontology based service recommendation system for social network. In this paper, implementation methods of the system are explained in detail. In order to extract user interests more exactly, the TF-IDF(term frequency-inverse document frequency) algorithm is improved according to the features of Microblogs and integrated with the TextRank algorithm. Also, we have improved the Hownet based semantic similarity algorithm with the consideration of the density of sememe tree. Experimental results show that recommendation results of our system can well reflect the real interests of users, and the improved algorithms can make the results more accurate.

关键词： Social Network Service Recommendation Ontology Microblog

作者: Li Ling Chen He Song Yingwei

作者单位: Jilin University College of communications Engineering Changchun,China

会议类型: 国际会议

会议名称: 2015 Fifth International Conference on Instrumentation and Measurement,Computer,Communication and Control (IMCCC2015)(第五届仪器测量、计算机通信与控制国际会议)

会议地点: 秦皇岛

会议语种:英文

页码: 1640-1644

在线出版日期: 2015-09-18（万方平台首次上网日期，不代表论文的发表时间）