Soft Computing in Information Retrieval
Subtitle: Techniques and Applications
By: edited by Fabio Crestani, Gabriella Pasi
Contributors: Pasi, Gabriella
Series: Studies in Fuzziness and Soft Computing -- 50; Studies in Fuzziness and Soft Computing -- 50
Publisher: Physica-Verlag HD; Imprint: Physica
Published: 2000
Place of publication: Heidelberg
Language: eng
Format: [electronic resource] :
Number of pages: 395
ISBN-13: 9783790824735; 9783790818499
Subjects: Information storage and retrieval systems; Computer science; Artificial intelligence; Management information systems
Description: Information retrieval (IR) aims at defining systems able to provide a fast and effective content-based access to a large amount of stored information. The aim of an IR system is to estimate the relevance of documents to users' information needs, expressed by means of a query. This is a very difficult and complex task, since it is pervaded with imprecision and uncertainty. Most of the existing IR systems offer a very simple model of IR, which privileges efficiency at the expense of effectiveness. A promising direction to increase the effectiveness of IR is to model the concept of "partially intrinsic" in the IR process and to make the systems adaptive, i.e. able to "learn" the user's concept of relevance. To this aim, the application of soft computing techniques can be of help to obtain greater flexibility in IR systems.
Notes: Online full text is restricted to subscribers.

Also available in print.

Mode of access: World Wide Web.
Table of contents: title: Fuzzy Set Theory; title: Neural Networks; title: Genetic Algorithms; title: Evidential and Probabilistic Reasoning; title: Rough Sets Theory, Multivalued Logics, and Other Approaches. The complete table of contents can be found on the Internet: http://www.springer.de.