【作者】 焦芬芬； 章勇；

【Author】 JIAO Fen-fen ZHANG Yong (College of Information Science and Technology,Nanjing University of Aeronautics & Astronautics,Nanjing,210016,China)

【机构】 南京航空航天大学信息科学与技术学院；

【摘要】 如何更好地帮助用户从过载信息中快速获取需要的信息一直是研究的热点,本文利用聚类分析技术和RSS标准,结合内容过滤和协同过滤的优点,提出了一种基于聚类分析的过滤算法- FUTC(Filtering using text clustering),同时引入了语义分析,利用Wordnet将文档内容表示成单词列表,综合语义相似度和主观评价相似度作为文档间相近程度的度量。FUTC算法能够有效的应用于RSS信息服务中,不仅可以准确高效地为用户提供感兴趣的信息,而且还能够为用户发掘新的兴趣信息。论文实现了一个个性化新闻阅读平台,并通过实验对算法有效性进行了验证。更多还原

【Abstract】 How to help people get information they need from a mass of Web information is always a research focus.Using RSS criterion and filtering algorithm,a novel filtering algorithm based on Clustering—filtering using text clustering(FUTC),which combines the advantage of content filtering and collaboration filtering,is proposed in this paper.Introducing semantic analysis,the algorithm represents the text as a word list using Wordnet,and integrates the Semantic similarity and user subjective evaluation similarity as the measure of document similarity.The algorithm FUTC is well applied in RSSbased information service,which ensuring not only provide users with accurate information,but also explore user’s new interest.To prove this method viable,a content filtering system based on RSS news, named RSS News Filtering,has been implemented.更多还原