期刊名称：International Journal of Soft Computing & Engineering
电子版ISSN：2231-2307
出版年度：2012
卷号：2
期号：2
页码：301-304
出版社：International Journal of Soft Computing & Engineering
摘要：The field of Information retrieval plays an important role in searching on the Internet. Most of the information retrieval systems are limited to the query processing based on keywords. In the information retrieval system matching of words with huge data is core task. Retrieval of the relevant natural language text document is of more challenging. In this paper we introduce the concept of OpenNLP tool for natural language processing of text for word matching. And in order to extract meaningful and query dependent information from large set of offline documents, data mining document clustering algorithm are adopted. Furthermore performance of the summary using OpenNLP tool and clustering techniques will be analysed and the optimal approach will be suggested.
关键词：K means algorithm; Document graph; Context;sensitive text summarization.
