Multi-Document News Web Page Summarization Using Content Extraction and Lexical Chain Based Key Phrase Extraction

In the area of text summarization, there have been significant advances recently. meantime, current trend in summarization is focused more on news summarization. Therefore, developing a synthesis approach capable extracting, comparing, and ranking sentences vital to create summary various articles context erroneous online data. It necessary, however, for system be able deal with multi-document summaries due content redundancy. This paper presents method summarizing web pages based similarity models sentence ranking, where relevant are extracted from original article. English-language collected five websites that cover same topic event. According our experimental results, provides better results than other recent methods news.