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Author Carpineto, Claudio
Title Concept Data Analysis : Theory and Applications
Imprint New York : John Wiley & Sons, Incorporated, 2004
©2004
book jacket
Edition 1st ed
Descript 1 online resource (221 pages)
text txt rdacontent
computer c rdamedia
online resource cr rdacarrier
Note Intro -- 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
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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Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2020. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries
Link Print version: Carpineto, Claudio Concept Data Analysis : Theory and Applications New York : John Wiley & Sons, Incorporated,c2004 9780470850558
Subject Computer science -- Mathematics.;Machine learning.;Information retrieval
Electronic books
Alt Author Romano, Giovanni
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