文章基本信息

标题：HIERARCHICAL DOCUMENT ORGANIZATION AND RETRIEVAL BASED ON THEMES FOR NEWS TRACKS
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作者：S. M. Arnica Sowmi ; D. Dinesh Babu
期刊名称：International Journal on Computer Science and Engineering
印刷版ISSN：2229-5631
电子版ISSN：0975-3397
出版年度：2013
卷号：5
期号：12
页码：940-948
出版社：Engg Journals Publications
摘要：Organizing text documents is an important task and there are also numbers of strategies available in it. A good document clustering approach can assist computers in organizing the document corpus automatically into a meaningful cluster hierarchy for efficient browsing and navigation, which is very valuable for overcoming the deficiencies of traditional information retrieval methods. By clustering the text documents, the documents sharing the same topic are grouped together. Unlike document classification, no labelled documents are provided in clustering. Hence clustering is also known as unsupervised learning. In case of term based data retrieval, time consumption problem prevails. This is because as for each term, the data set�s has to be retrieved. Hence we are going for taxonomy based data retrieval. This paper presents the taxonomical approach of clustering data set in a dynamic environment. It is a difficult task to cluster data in a dynamic environment. But this can be made easily by using RSS feeds.
关键词：ANITA approach; CHRONICLE construction; RSS feeds; Taxonomical clustering.