摘要
针对现有检索系统存在的问题,对个性化检索技术进行了深入的研究,提出了一种基于多Agent的分布式个性化检索系统模型(MADSS)。系统以用户个性化模型为中心,分别对用户的请求、检索结果和用户行为三个方面进行个性化处理,使信息检索的效果有了明显提高;结合分布式的多Agent技术、相关反馈数据融合技术和Personalized PageRank排序算法,能有效地解决系统在交互方式、自适应用户兴趣和信息源变化、高效并行检索等方面的不足,具有很好的理论价值和应用价值。
This paper describes the architecture of a personalized retrieval system（MADSS）.The Distributed multi-agent technique,information filtering technique and personalized pagerank technique based on personalized models are utilized,which makes the system more efficient.Compared with the systems mentioned in the references,this system has the features of adjusting to shifting user＇ s interests and changing source adaptively,as well as in intelligently searching good results.The results show that this system generally can be used in the electronic business and information retrieval in Internet and have high significance in theories and applications.
出处
《情报科学》
CSSCI
北大核心
2010年第4期579-583,共5页
Information Science
关键词
信息检索
个性化检索
分布式
AGENT
information retrieval
personalized retrieval
distributed
agent
