| 書目名稱 | Information Retrieval: Uncertainty and Logics |
| 副標(biāo)題 | Advanced Models for |
| 編輯 | Fabio Crestani,Mounia Lalmas,Cornelis Joost Rijsbe |
| 視頻video | http://file.papertrans.cn/466/465228/465228.mp4 |
| 叢書名稱 | The Information Retrieval Series |
| 圖書封面 |  |
| 描述 | In recent years, there have been several attempts to define alogic for information retrieval (IR). The aim was to provide a richand uniform representation of information and its semantics with thegoal of improving retrieval effectiveness. The basis of a logicalmodel for IR is the assumption that queries and documents can berepresented effectively by logical formulae. To retrieve a document,an IR system has to infer the formula representing the query from theformula representing the document. This logical interpretation ofquery and document emphasizes that relevance in IR is an inferenceprocess. .The use of logic to build IR models enables one to obtain models thatare more general than earlier well-known IR models. Indeed, somelogical models are able to represent within a uniform frameworkvarious features of IR systems such as hypermedia links, multimediadata, and user‘s knowledge. Logic also provides a common approach tothe integration of IR systems with logical database systems. Finally,logic makes it possible to reason about an IR model and itsproperties. This latter possibility is becoming increasingly moreimportant since conventional evaluation methods, although goodindicators |
| 出版日期 | Book 1998 |
| 關(guān)鍵詞 | database; database systems; information; information retrieval; multimedia |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-1-4615-5617-6 |
| isbn_softcover | 978-1-4613-7570-8 |
| isbn_ebook | 978-1-4615-5617-6Series ISSN 1871-7500 Series E-ISSN 2730-6836 |
| issn_series | 1871-7500 |
| copyright | Kluwer Academic Publishers 1998 |
|Archiver|手機(jī)版|小黑屋|
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