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Concept Data Analysis : Theory and Applications - Claudio Carpineto

Concept Data Analysis

Theory and Applications

Hardcover Published: 3rd September 2004
ISBN: 9780470850558
Number Of Pages: 220

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With the advent of the Web along with the unprecedented amount of information available in electronic format, conceptual data analysis is more useful and practical than ever, because this technology addresses important limitations of the systems that currently support users in their quest for information. <i>Concept Data Analysis: Theory &amp; Applications</i> is the first book that provides a comprehensive treatment of the full range of algorithms available for conceptual data analysis, spanning creation, maintenance, display and manipulation of concept lattices.&#160; The accompanying&#160;website allows you to gain a greater understanding of the principles covered in the book through actively working on the topics discussed. <p> The three main areas explored are interactive mining of documents or collections of documents (including Web documents), automatic text ranking, and rule mining from structured data.&#160; The potentials of conceptual data analysis in the application areas being considered are further illustrated by&#160;two detailed case studies. <p> <i>Concept Data Analysis: Theory &amp; Applications</i> is essential for researchers active in information processing and management and industry practitioners who are interested in creating a commercial product for conceptual data analysis or developing content management applications.&#160;<br>

Foreword.

Preface.

I: THEORY AND ALGORITHMS.

1. Theoretical Foundations.

1.1 Basic Notions of Orders and Lattices.

1.2 Context, Concept, and Concept Lattice.

1.3 Many-valued Contexts.

1.4 Bibliographic Notes.

2. Algorithms.

2.1 Constructing Concept Lattices.

2.2 Incremental Lattice Update.

2.3 Visualization.

2.4 Adding Knowledge to Concept Lattices.

2.5 Bibliographic Notes.

II: APPLICATIONS.

3. Information Retrieval.

3.1 Query Modification.

3.2 Document Ranking

4. Text Mining.

4.1 Mining the Content of the ACM Digital Library.

4.2 MiningWeb Retrieval Results with CREDO.

4.3 Bibliographic Notes.

5. Rule Mining.

5.1 Implications.

5.2 Functional Dependencies.

5.3 Association Rules.

5.4 Classification Rules.

5.5 Bibliographic Notes.

References.

Index.

ISBN: 9780470850558
ISBN-10: 0470850558
Audience: Professional
Format: Hardcover
Language: English
Number Of Pages: 220
Published: 3rd September 2004
Publisher: John Wiley and Sons Ltd
Country of Publication: US
Dimensions (cm): 25.3 x 17.6  x 1.8
Weight (kg): 0.57
Edition Number: 1