Description

Book Synopsis
Offers a treatment of the full range of algorithms available for conceptual data analysis, spanning creation, maintenance, display and manipulation of concept lattices. The website accompanying this book allows you to gain a better understanding of the principles covered herein through working on the topics discussed.

Table of Contents
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.

Concept Data Analysis

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    A Hardback by Claudio Carpineto, Giovanni Romano

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      Book details

      Publisher John Wiley & Sons Inc
      Published 27 July 2004
      ISBN-13 9780470850558
      978-0470850558
      ISBN-10 0470850558
      Also in:
      Computer networking and communications

      Description

      Book Synopsis
      Offers a treatment of the full range of algorithms available for conceptual data analysis, spanning creation, maintenance, display and manipulation of concept lattices. The website accompanying this book allows you to gain a better understanding of the principles covered herein through working on the topics discussed.

      Table of Contents
      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.

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