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Jones, K.: Linguistic searching versus relevance ranking : DR-LINK and TARGET (1999)
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- Source
- Online and CD-ROM review. 23(1999) no.2, S.67-80
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Belkin, N.J.; Cool, C.; Koenemann, J.; Ng, K.B.; Park, S.: Using relevance feedback and ranking in interactive searching (1996)
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- Pages
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Clarke, C.L.A.; Cormack, G.V.; Burkowski, F.J.: Shortest substring ranking : multitext experiments for TREC-4 (1996)
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- Pages
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- The Fourth Text Retrieval Conference (TREC-4). Ed.: K. Harman
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Savoy, J.; Ndarugendamwo, M.; Vrajitoru, D.: Report on the TREC-4 experiment : combining probabilistic and vector-space schemes (1996)
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- Pages
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- The Fourth Text Retrieval Conference (TREC-4). Ed.: K. Harman
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Koopman, R.: ¬Ein OPAC mit Gewichtungsalgorithmen : Der PICA Micro OPC (1996)
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- Pages
- S.95-105
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- Zukunft der Sacherschließung im OPAC: Vorträge des 2. Düsseldorfer OPAC-Kolloquiums am 21. Juni 1995. Hrsg.: E. Niggemann u. K. Lepsky
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Faloutsos, C.: Signature files (1992)
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- Date
- 7. 5.1999 15:22:48
- Pages
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Chang, C.-H.; Hsu, C.-C.: Integrating query expansion and conceptual relevance feedback for personalized Web information retrieval (1998)
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- Date
- 1. 8.1996 22:08:06
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- Computer networks and ISDN systems. 30(1998) nos.1/7, S.621-623
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Joss, M.W.; Wszola, S.: ¬The engines that can : text search and retrieval software, their strategies, and vendors (1996)
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- Date
- 12. 9.1996 13:56:22
- Source
- CD-ROM professional. 9(1996) no.6, S.30+(14 S.)
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Kelledy, F.; Smeaton, A.F.: Signature files and beyond (1996)
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- Pages
- S.124-144
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- Information retrieval: new systems and current research. Proceedings of the 16th Research Colloquium of the British Computer Society Information Retrieval Specialist Group, Drymen, Scotland, 22-23 Mar 94. Ed.: R. Leon
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Kantor, P.; Kim, M.H.; Ibraev, U.; Atasoy, K.: Estimating the number of relevant documents in enormous collections (1999)
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- Pages
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Burgin, R.: ¬The retrieval effectiveness of 5 clustering algorithms as a function of indexing exhaustivity (1995)
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- Date
- 22. 2.1996 11:20:06
- Source
- Journal of the American Society for Information Science. 46(1995) no.8, S.562-572
-
Efthimiadis, E.N.: User choices : a new yardstick for the evaluation of ranking algorithms for interactive query expansion (1995)
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- Date
- 22. 2.1996 13:14:10
- Source
- Information processing and management. 31(1995) no.4, S.605-620
-
Cross-language information retrieval (1998)
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- Content
- Enthält die Beiträge: GREFENSTETTE, G.: The Problem of Cross-Language Information Retrieval; DAVIS, M.W.: On the Effective Use of Large Parallel Corpora in Cross-Language Text Retrieval; BALLESTEROS, L. u. W.B. CROFT: Statistical Methods for Cross-Language Information Retrieval; Distributed Cross-Lingual Information Retrieval; Automatic Cross-Language Information Retrieval Using Latent Semantic Indexing; EVANS, D.A. u.a.: Mapping Vocabularies Using Latent Semantics; PICCHI, E. u. C. PETERS: Cross-Language Information Retrieval: A System for Comparable Corpus Querying; YAMABANA, K. u.a.: A Language Conversion Front-End for Cross-Language Information Retrieval; GACHOT, D.A. u.a.: The Systran NLP Browser: An Application of Machine Translation Technology in Cross-Language Information Retrieval; HULL, D.: A Weighted Boolean Model for Cross-Language Text Retrieval; SHERIDAN, P. u.a. Building a Large Multilingual Test Collection from Comparable News Documents; OARD; D.W. u. B.J. DORR: Evaluating Cross-Language Text Filtering Effectiveness
- Footnote
- Rez. in: Machine translation review: 1999, no.10, S.26-27 (D. Lewis): "Cross Language Information Retrieval (CLIR) addresses the growing need to access large volumes of data across language boundaries. The typical requirement is for the user to input a free form query, usually a brief description of a topic, into a search or retrieval engine which returns a list, in ranked order, of documents or web pages that are relevant to the topic. The search engine matches the terms in the query to indexed terms, usually keywords previously derived from the target documents. Unlike monolingual information retrieval, CLIR requires query terms in one language to be matched to indexed terms in another. Matching can be done by bilingual dictionary lookup, full machine translation, or by applying statistical methods. A query's success is measured in terms of recall (how many potentially relevant target documents are found) and precision (what proportion of documents found are relevant). Issues in CLIR are how to translate query terms into index terms, how to eliminate alternative translations (e.g. to decide that French 'traitement' in a query means 'treatment' and not 'salary'), and how to rank or weight translation alternatives that are retained (e.g. how to order the French terms 'aventure', 'business', 'affaire', and 'liaison' as relevant translations of English 'affair'). Grefenstette provides a lucid and useful overview of the field and the problems. The volume brings together a number of experiments and projects in CLIR. Mark Davies (New Mexico State University) describes Recuerdo, a Spanish retrieval engine which reduces translation ambiguities by scanning indexes for parallel texts; it also uses either a bilingual dictionary or direct equivalents from a parallel corpus in order to compare results for queries on parallel texts. Lisa Ballesteros and Bruce Croft (University of Massachusetts) use a 'local feedback' technique which automatically enhances a query by adding extra terms to it both before and after translation; such terms can be derived from documents known to be relevant to the query.
- Pages
- VII,182 S
- Type
- s
-
Robertson, S.E.; Sparck Jones, K.: Simple, proven approaches to text retrieval (1997)
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-
Reddaway, S.: High speed text retrieval from large databases on a massively parallel processor (1991)
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