As data reported by humans about our world, text data play a very important role in all data
mining applications, yet how to develop a general text analysis system to sup-port all text …

In this chapter, we introduce latent semantic analysis (LSA), which uses singular value
decomposition (SVD) to reduce the dimensionality of the document-term representation …

Analyzing textual data is a very challenging task because of the huge volume of data
generated daily. Fundamental issues in text analysis include the lack of structure in …

The SCISOR. system is a computer program designed to scan naturally occurring texts in
constrained domains, extract information, and answer questions about that information. The …

Text Analytics: Boon to Knowledge Management? Page 1 87 Information Systems
Management, 26: 87 Copyright © Taylor & Francis Group, LLC ISSN: 1058-0530 print/1934-8703 …

Until the recent past, there have been two extreme approaches toward extracting knowledge
from text. On the one hand, artificial intelligence systems have long operated under the …

Abstract Latent Semantic Analysis (LSA) is a technique for comparing texts using a vector-
based representation that is learned from a corpus. This article begins with a description of …

Experimenting with different mathematical objects for text representation is an important step
of building text classification models. In order to be efficient, such objects of a formal model …

This chapter looks at the philosophical and methodological issues of unstructured text data.
Text data mining allows for a much faster organization and analysis of text data than what …

A lot of attention has been paid recently to the development of tools and concepts that allow
computer-based analysis oftexts. Latemodel text management programs help you code text …