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.
General
| Imprint: |
Physica-Verlag
|
| Country of origin: |
Germany |
| Series: |
Studies in Fuzziness and Soft Computing, 50 |
| Release date: |
October 2010 |
| First published: |
2000 |
| Editors: |
Fabio Crestani
• Gabriella Pasi
|
| Dimensions: |
235 x 155 x 21mm (L x W x T) |
| Format: |
Paperback
|
| Pages: |
396 |
| Edition: |
Softcover reprint of hardcover 1st ed. 2000 |
| ISBN-13: |
978-3-7908-2473-5 |
| Categories: |
Books >
Computing & IT >
Applications of computing >
Databases >
General
|
| LSN: |
3-7908-2473-9 |
| Barcode: |
9783790824735 |
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