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 dif...

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Bibliographische Detailangaben

Weitere Verfasser:	Crestani, Fabio 1962- (HerausgeberIn), Pasi, Gabriella 1961- (HerausgeberIn)
Format:	Elektronisch E-Book
Sprache:	English
Veröffentlicht:	Heidelberg Physica-Verlag HD 2000
Schriftenreihe:	Studies in Fuzziness and Soft Computing 50
Schlagworte:	Computer Science Information Storage and Retrieval Artificial Intelligence (incl. Robotics) IT in Business Computer science Information technology Business / Data processing Information storage and retrieval Artificial intelligence Information Retrieval Soft Computing Aufsatzsammlung
Online-Zugang:	BTU01 FHI01 Volltext
Zusammenfassung:	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
Beschreibung:	1 Online-Ressource (XII, 396 p)
ISBN:	9783790818499
DOI:	10.1007/978-3-7908-1849-9