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 qpartially intrinsicq in the IR process and to make the systems adaptive, i.e. able to qlearnq 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.Techniques and Applications Fabio Crestani Gabriella Pasi. Document Classification with Unsupervised Artificial Neural Networks Dieter Merkl and Andreas Rauber Institut fur Softwaretechnik Technische Universitat Wien Resselgasse 3/188, anbsp;...
|Title||:||Soft Computing in Information Retrieval|
|Publisher||:||Springer Science & Business Media - 2000-05-26|