Soft Computing in Information Retrieval Techniques and Applications /

• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Άλλοι συγγραφείς: Crestani, Fabio (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt), Pasi, Gabriella (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Heidelberg : Physica-Verlag HD : Imprint: Physica, 2000.
• Έκδοση: 1st ed. 2000.
• Σειρά: Studies in Fuzziness and Soft Computing, 50
• Θέματα: Information storage and retrieval.; Artificial intelligence.; Information technology.; Business-Data processing.; Information Storage and Retrieval.; Artificial Intelligence.; IT in Business.
• Φυσική περιγραφή: XII, 396 p. online resource.
• ISBN: 9783790818499
• ISSN: 1434-9922 ;
• DOI: 10.1007/978-3-7908-1849-9

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.