摘要
对社会网络环境下构建个性化推荐系统的现有技术进行综述。介绍社会网络的基本概念,简述推荐系统的应用领域和目前面临的挑战,重点介绍社会化推荐的相关技术的研究现状,包括用户生成内容、社会化标签推荐、博客挖掘和基于信任的推荐,分析社会化推荐面临的主要问题。利用Web 2.0环境下的用户生成内容,为解决用户配置和冷启动问题提供一个研究方向。
Gives an overview of existing technologies for building personalized recommender systems in social networking environment. Introduces the basic concepts of the social networks. Presentes the application fields and challenges of the recommender systems. Specially, reviews the relevant techniques for building recommender system in social networking context, including user generated content, social tagging system, blog mining, trust-based recommender system, analyzes the main problem confronted in social recommendation. Proposes a research direction for addressing user profiling and cold start problems by exploiting user-generated content （UGC） newly available in Web 2.0.
基金
教育部春晖计划(No.Z2011088)
四川省教育厅重点项目(No.11ZB002)
西华大学网络智能信息处理省高校实验室基金(No.SZJJ2012-027)
关键词
社会网络
推荐系统
用户配置
用户生成内容
Social Networking
Recommender System
User Profiles
User Generated Content
