Content Extraction with text mining using natural language processing for anatomy based topic summarization

Journal Title: International Journal of Modern Engineering Research (IJMER) - Year 2013, Vol 3, Issue 1

Abstract

 Abstract: Inorder to get exact content for the web browsers when searching for some information we have combined two methods together.The first method is text mining using natural language processing and parse tree query language, the second method is TSCAN (Topic summarization and Content Anatomy).In the first method, when a sentence is given for searching, the sentence is converted into a automatic query formation using natural language processing tools and information is retrieved using text mining methods.In the second method a temporal similarity (TS) function is implemented to generate the event dependencies and context similarity to form an evolution graph of the topic search.Both methods are integrated together to make the quality of the extraction of required content efficient and easier.

Authors and Affiliations

K. Fouzia Sulthana

Keywords

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  • EP ID EP103948
  • DOI -
  • Views 107
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How To Cite

K. Fouzia Sulthana (2013).  Content Extraction with text mining using natural language processing for anatomy based topic summarization. International Journal of Modern Engineering Research (IJMER), 3(1), 564-567. https://europub.co.uk./articles/-A-103948