| 000 | 03151nam a22005055i 4500 | ||
|---|---|---|---|
| 001 | 978-1-4020-3768-9 | ||
| 003 | DE-He213 | ||
| 005 | 20251006084459.0 | ||
| 007 | cr nn 008mamaa | ||
| 008 | 100301s2005 ne | s |||| 0|eng d | ||
| 020 | _a9781402037689 | ||
| 020 | _a99781402037689 | ||
| 024 | 7 |
_a10.1007/1-4020-3768-6 _2doi |
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| 082 | 0 | 4 |
_a004 _223 |
| 100 | 1 |
_aKruschwitz, Udo. _eauthor. |
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| 245 | 1 | 0 |
_aIntelligent Document Retrieval _h[electronic resource] : _bExploiting Markup Structure / _cby Udo Kruschwitz. |
| 264 | 1 |
_aDordrecht : _bSpringer Netherlands, _c2005. |
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| 300 |
_aXVI, 197 p. _bonline resource. |
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| 336 |
_atext _btxt _2rdacontent |
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| 337 |
_acomputer _bc _2rdamedia |
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| 338 |
_aonline resource _bcr _2rdacarrier |
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| 347 |
_atext file _bPDF _2rda |
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| 490 | 1 |
_aThe Springer International Series On Information Retrieval, _x1387-5264 ; _v17 |
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| 505 | 0 | _aRelated Work -- Data Analysis and Domain Model Construction -- Incorporating Additional Knowledge -- A Dialogue System for Partially Structured Data -- UKSearch - Intelligent Web Search -- UKSearch - Evaluation and Discussion -- YPA - Searching Classified Directories -- Future Directions and Conclusions. | |
| 520 | _aCollections of digital documents can nowadays be found everywhere in institutions, universities or companies. Examples are Web sites or intranets. But searching them for information can still be painful. Searches often return either large numbers of matches or no suitable matches at all. Such document collections can vary a lot in size and how much structure they carry. What they have in common is that they typically do have some structure and that they cover a limited range of topics. The second point is significantly different from the Web in general. The type of search system that we propose in this book can suggest ways of refining or relaxing the query to assist a user in the search process. In order to suggest sensible query modifications we would need to know what the documents are about. Explicit knowledge about the document collection encoded in some electronic form is what we need. However, typically such knowledge is not available. So we construct it automatically. | ||
| 650 | 0 | _aCOMPUTER SCIENCE. | |
| 650 | 0 | _aCOMPUTER SYSTEM PERFORMANCE. | |
| 650 | 0 | _aINFORMATION STORAGE AND RETRIEVAL SYSTEMS. | |
| 650 | 0 | _aINFORMATION SYSTEMS. | |
| 650 | 0 | _aTEXT PROCESSING (COMPUTER SCIENCE. | |
| 650 | 1 | 4 | _aCOMPUTER SCIENCE. |
| 650 | 2 | 4 | _aCOMPUTER SCIENCE, GENERAL. |
| 650 | 2 | 4 | _aSYSTEM PERFORMANCE AND EVALUATION. |
| 650 | 2 | 4 | _aINFORMATION STORAGE AND RETRIEVAL. |
| 650 | 2 | 4 | _aINFORMATION SYSTEMS APPLICATIONS (INCL.INTERNET). |
| 650 | 2 | 4 | _aDOCUMENT PREPARATION AND TEXT PROCESSING. |
| 710 | 2 | _aSpringerLink (Online service) | |
| 773 | 0 | _tSpringer eBooks | |
| 776 | 0 | 8 |
_iPrinted edition: _z9781402037672 |
| 830 | 0 |
_aThe Springer International Series On Information Retrieval, _x1387-5264 ; _v17 |
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| 856 | 4 | 0 |
_uhttp://dx.doi.org/10.1007/1-4020-3768-6 _zVer el texto completo en las instalaciones del CICY |
| 912 | _aZDB-2-SCS | ||
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_2ddc _cER |
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_c60595 _d60595 |
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