1.

Record Nr.

UNINA9910293146803321

Autore

Berthold Michael R

Titolo

Bisociative Knowledge Discovery [[electronic resource] ] : An Introduction to Concept, Algorithms, Tools, and Applications / / edited by Michael R. Berthold

Pubbl/distr/stampa

Cham, : Springer Nature, 2012

Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2012

ISBN

3-642-31830-4

Edizione

[1st ed. 2012.]

Descrizione fisica

1 online resource (IX, 485 p. 146 illus.)

Collana

Lecture Notes in Artificial Intelligence ; ; 7250

Disciplina

006.3/12

Soggetti

Artificial intelligence

Data mining

Application software

User interfaces (Computer systems)

Pattern recognition

Computer communication systems

Artificial Intelligence

Data Mining and Knowledge Discovery

Information Systems Applications (incl. Internet)

User Interfaces and Human Computer Interaction

Pattern Recognition

Computer Communication Networks

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Note generali

Bibliographic Level Mode of Issuance: Monograph

Nota di bibliografia

Includes bibliographical references and index.

Sommario/riassunto

Modern knowledge discovery methods enable users to discover complex patterns of various types in large information repositories. However, the underlying assumption has always been that the data to which the methods are applied originates from one domain.   The focus of this book, and the BISON project from which the contributions originate, is a network-based integration of various types of data repositories and the development of new ways to analyse and explore



the resulting gigantic information networks. Instead of seeking well-defined global or local patterns, the aim was to find domain-bridging associations. These are particularly interesting if they are sparse and have not been encountered before.   The 32 contributions presented in this state-of-the-art survey, together with a detailed introduction to the book, are organized in topical sections on bisociation; representation and network creation; network analysis; exploration; and applications and evaluation.  .