Concept Data Analysis: Theory and Applications

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.