| 书目名称 | Soft Computing in Information Retrieval |
| 副标题 | Techniques and Appli |
| 编辑 | Fabio Crestani,Gabriella Pasi |
| 视频video | |
| 丛书名称 | Studies in Fuzziness and Soft Computing |
| 图书封面 |  |
| 描述 | 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. |
| 出版日期 | Book 2000 |
| 关键词 | Bayesian network; algorithms; classification; data mining; fuzzy; fuzzy sets; genetic algorithms; informati |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-3-7908-1849-9 |
| isbn_softcover | 978-3-7908-2473-5 |
| isbn_ebook | 978-3-7908-1849-9Series ISSN 1434-9922 Series E-ISSN 1860-0808 |
| issn_series | 1434-9922 |
| copyright | Physica-Verlag Heidelberg 2000 |
发表于 2025-3-21 19:53:06
