期刊名称：International Journal of Advanced Research In Computer Science and Software Engineering
印刷版ISSN：2277-6451
电子版ISSN：2277-128X
出版年度：2013
卷号：3
期号：8
出版社：S.S. Mishra
摘要：In the internet searching for a specific topic it contains some type of events and activities .The topic contains more documents in the search engine about a specific type of topic, topic anatomy is define summarizes and associat es the core parts of a topic temporally so that readers can understand the content easily. The existing topic anatomy model, called TSCAN, evolves the major themes of a topic from the eigenvectors of a temporal block association matrix. Then, the similarity of events of the themes and their summaries are extracted by examining the constitution of the eigenvectors. Finally, the events which are extracted are associated through their temporal closeness and context similarity to form an evolution graph of the topic. Experiments found on the official TDT4 corpus demonstrate that the generated temporal summaries present the storylines of topics in a comprehensible form. The proposed framework contains ranking for a specific topics and contents, by this process it give usefulness of topic anatomy
关键词：searching topic; text mining; language summarization; ranking; graph construction
