Intelligent Document Retrieval Exploiting Markup Structure /

Collections 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 docume...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριος συγγραφέας: Kruschwitz, Udo (Συγγραφέας)
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Dordrecht : Springer Netherlands, 2005.
Σειρά:The Springer International Series On Information Retrieval, 17
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
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100 1 |a Kruschwitz, Udo.  |e author. 
245 1 0 |a Intelligent Document Retrieval  |h [electronic resource] :  |b Exploiting Markup Structure /  |c by Udo Kruschwitz. 
264 1 |a Dordrecht :  |b Springer Netherlands,  |c 2005. 
300 |a XVI, 198 p.  |b online resource. 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
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347 |a text file  |b PDF  |2 rda 
490 1 |a The Springer International Series On Information Retrieval,  |x 1387-5264 ;  |v 17 
505 0 |a Related 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 |a Collections 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 |a Computer science. 
650 0 |a Computer system failures. 
650 0 |a Computers. 
650 0 |a Information storage and retrieval. 
650 0 |a Text processing (Computer science). 
650 1 4 |a Computer Science. 
650 2 4 |a Theory of Computation. 
650 2 4 |a Computer Science, general. 
650 2 4 |a Information Storage and Retrieval. 
650 2 4 |a System Performance and Evaluation. 
650 2 4 |a Information Systems Applications (incl. Internet). 
650 2 4 |a Document Preparation and Text Processing. 
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776 0 8 |i Printed edition:  |z 9781402037672 
830 0 |a The Springer International Series On Information Retrieval,  |x 1387-5264 ;  |v 17 
856 4 0 |u http://dx.doi.org/10.1007/1-4020-3768-6  |z Full Text via HEAL-Link 
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950 |a Computer Science (Springer-11645)