Emerging Technologies of Text Mining: Techniques and Applications, 1st Edition

  • Published By:
  • ISBN-10: 1599043750
  • ISBN-13: 9781599043753
  • Grade Level Range: College Freshman - College Senior
  • 358 Pages | eBook
  • Original Copyright 2007 | Published/Released December 2007
  • This publication's content originally published in print form: 2007

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About

Overview

Massive amounts of textual data make up most organizations' stored information. Therefore, there is increasingly high demand for a comprehensive resource providing practical hands-on knowledge for real-world applications.

Emerging Technologies of Text Mining: Techniques and Applications provides the most recent technical information related to the computational models of the text mining process, discussing techniques within the realms of classification, association analysis, information extraction, and clustering. Offering an innovative approach to the utilization of textual information mining to maximize competitive advantage, Emerging Technologies of Text Mining will provide libraries with the defining reference on this topic.

Table of Contents

Front Cover.
Title Page.
Copyright Page.
Other Frontmatter.
Table of Contents.
Detailed Table of Contents.
Foreword.
Other Frontmatter.
Preface.
Acknowledgment.
1: Information Extraction: Methodologies and Applications.
2: Creating Strategic Information for Organizations with Structured Text.
3: Automatic NLP for Competitive Intelligence.
4: Mining Profiles and Definitions with Natural Language Processing.
5: Deriving Taxonomy from Documents at Sentence Level.
6: Rule Discovery from Textual Data.
7: Exploring Unclassified Texts Using Multiview Semisupervised Learning.
8: A Multi-Agent Neural Network System for Web Text Mining.
9: Contextualized Clustering in Exploratory Web Search.
10: AntWeb—Web Search Based on Ant Behavior: Approach and Implementation in Case of Interlegis.
11: Conceptual Clustering of Textual Documents and Some Insights for Knowledge Discovery.
12: A Hierarchical Online Classifier for Patent Categorization.
13: Text Mining to Define a Validated Model of Hospital Rankings.
14: An Interpretation Process for Clustering Analysis Based on the Ontology of Language.
Compilation of References.
About the Contributors.
Index.