A Statistical Approach to perform Web Based Summarization
Journal Title: IOSR Journals (IOSR Journal of Computer Engineering) - Year 2012, Vol 1, Issue 5
Abstract
Over the past decade more and more users of the Internet rely on the search engines to help them find the information they need. However the information they find depends to a large extent, on the ranking mechanism of the search engines they use. Not surprisingly it in general consists of a large amount of information that is completely irrelevant. Text summarization is a process of reducing the size of a text while preserving its information content. Text Summarization is an emerging technique for understanding the main purpose of any kind of documents. To visualize a large text document within a short duration and small area like PDA screen, summarization provides a greater flexibility and convenience. This research focuses on developing a statistical automatic text summarization approach, K-mixture probabilistic model, to enhancing the quality of summaries. Sentences are ranked and extracted based on their semantic relationships significance values. The objective of this research is thus to propose a statistical approach to text summarization.
Authors and Affiliations
Kirti Bhatia
Keywords
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