Concept Data Analysis -- 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 -- 2.1.1 Computational space complexity of concept lattices -- 2.1.2 Construction of the set of concepts -- 2.1.3 Construction of concept lattices -- 2.1.4 Construction of partial concept lattices -- 2.2 Incremental Lattice Update -- 2.2.1 Incremental construction of concept lattices -- 2.2.2 Updating the context -- 2.2.3 Summary of lattice construction -- 2.3 Visualization -- 2.3.1 Hierarchical folders -- 2.3.2 Nested line diagrams -- 2.3.3 Focus+context views -- 2.4 Adding Knowledge to Concept Lattices -- 2.4.1 Adding background knowledge to object description -- 2.4.2 Pruning concepts with user constraints -- 2.5 Bibliographic Notes -- II Applications -- 3 Information Retrieval -- 3.1 Query Modification -- 3.1.1 Navigating around the query concept -- 3.1.2 Thesaurus-enhanced navigation and querying -- 3.1.3 Automatic generation of index terms -- 3.2 Document Ranking -- 3.2.1 The vocabulary problem -- 3.2.2 Concept lattice-based ranking -- 3.2.3 Scalability -- 3.3 Bibliographic Notes -- 4 Text Mining -- 4.1 Mining the Content of the ACM Digital Library -- 4.1.1 The ACM Digital Library -- 4.1.2 Information retrieval and data view versus text mining -- 4.1.3 Constructing the TOIS concept lattice -- 4.1.4 Interacting with the TOIS concept lattice -- 4.2 Mining Web Retrieval Results with CREDO -- 4.2.1 Visualizing Web retrieval results -- 4.2.2 Design and implementation of CREDO -- 4.2.3 Example sessions -- 4.3 Bibliographic Notes -- 5 Rule Mining -- 5.1 Implications -- 5.1.1 Computational space complexity of implications.

5.1.2 Generating implications from the concept lattice -- 5.2 Functional Dependencies -- 5.2.1 Functional dependencies as implications of transformed contexts -- 5.2.2 Computational space complexity of the concept lattice of transformed contexts -- 5.3 Association Rules -- 5.3.1 Mining frequent concepts -- 5.3.2 Generating confident rules from frequent concepts -- 5.4 Classification Rules -- 5.5 Bibliographic Notes -- References -- Index.