Chapter

Natural Language Processing and Information Systems

Volume 5723 of the series Lecture Notes in Computer Science pp 301-302

Improving Full Text Search with Text Mining Tools

  • Scott PiaoAffiliated withNational Centre for Text Mining, School of Computer Science, The University of Manchester
  • , Brian ReaAffiliated withNational Centre for Text Mining, School of Computer Science, The University of Manchester
  • , John McNaughtAffiliated withNational Centre for Text Mining, School of Computer Science, The University of Manchester
  • , Sophia AnaniadouAffiliated withNational Centre for Text Mining, School of Computer Science, The University of Manchester

Abstract

Today, academic researchers face a flood of information. Full text search provides an important way of finding useful information from mountains of publications, but it generally suffers from low precision, or low quality of document retrieval. A full text search algorithm typically examines every word in a given text, trying to find the query words. Unfortunately, many words in natural language are polysemous, and thus many documents retrieved using this approach are irrelevant to actual search queries.

Keywords

Information Retrieval Full Text Search Term extraction Termine Document clustering Natural Language processing