Conceptual Exploration / by Bernhard Ganter, Sergei Obiedkov
By: Ganter, Bernhard
Contributor(s): SpringerLink (Online service)
| Obiedkov, Sergei, autor
Material type:
E-bookPublisher: Berlin, Heidelberg : Springer Berlin Heidelberg, 2016Description: 1 recurso en línea (XVII, 315 p.) : 148 ilustraciones.ISBN: 9783662492918.Subject: Data mining
| Item type | Current library | Collection | Call number | Copy number | Status | Date due | Barcode | Item holds | |
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Madrid Digital Acceso Electrónico (UEM) | Ciencias e Ingeniería | QA76.9.D343 G368 2016 EB (Browse shelf(Opens below)) | .i11599716 | Acceso electrónico | eBOOK .i11599716 |
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| QA76.9 .D343 C667 2015 EB Computational Intelligence in Data Mining - Volume 2 Proceedings of the International Conference on CIDM, 20-21 December 2014 | QA76.9.D343 ES Data Mining and Knowledge Discovery | QA76.9.D343 E447 2018 EB Emerging Ideas on Information Filtering and Retrieval DART 2013: Revised and Invited Papers | QA76.9.D343 G368 2016 EB Conceptual Exploration | QA76.9.D343 H47 2016 EB Multilabel Classification : Problem Analysis, Metrics and Techniques | QA76.9.D343 H665 2017 EB Granular-relational data mining : how to mine relational data in the paradigm of granular computing? | QA76.9.D343 H834 2016 EB Fuzziness in Information Systems : How to Deal with Crisp and Fuzzy Data in Selection, Classification, and Summarization |
What to expect from this book -- Concept lattices -- An algorithm for closure systems -- The canonical basis -- Attribute exploration -- Non-implicational background knowledge -- Enhancing the expressive power -- Relational Exploration -- Concept exploration
This is the first textbook on attribute exploration, its theory, its algorithms for applications, and some of its many possible generalizations. Attribute exploration is useful for acquiring structured knowledge through an interactive process, by asking queries to an expert. Generalizations that handle incomplete, faulty, or imprecise data are discussed, but the focus lies on knowledge extraction from a reliable information source. The method is based on Formal Concept Analysis, a mathematical theory of concepts and concept hierarchies, and uses its expressive diagrams. The presentation is self-contained. It provides an introduction to Formal Concept Analysis with emphasis on its ability to derive algebraic structures from qualitative data, which can be represented in meaningful and precise graphics
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