Info iconThis preview shows page 1. Sign up to view the full content.

View Full Document Right Arrow Icon
This is the end of the preview. Sign up to access the rest of the document.

Unformatted text preview: e available. There are estimates that 85% of business information lives in the form of text (TMS05 2005). Unfortunately, the usual logic-based programming paradigm has great difficulties in capturing the fuzzy and often ambiguous relations in text documents. Text mining aims at disclosing the concealed information by means of methods which on the one hand are able to cope with the large number of words and structures in natural language and on the other hand allow to handle vagueness, uncertainty and fuzziness. In this paper we describe text mining as a truly interdisciplinary method drawing on information retrieval, machine learning, statistics, computational linguistics and especially data mining. We first give a short sketch of these methods and then define text mining in relation to them. Later sections survey state of the art approaches for the main analysis tasks preprocessing, classification, clustering, information extraction and visualization. The last section exemplifies text mining in the context of a number...
View Full Document

This note was uploaded on 06/19/2011 for the course IT 2258 taught by Professor Aymenali during the Summer '11 term at Abu Dhabi University.

Ask a homework question - tutors are online