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1
TREC 2008 at the University at Buffalo: Legal and Blog Track
In: DTIC (2008)
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2
Overview of the CLEF-2006 cross-language speech retrieval track
In: Oard, Douglas W., Wang, Jianqiang, Jones, Gareth J.F. orcid:0000-0003-2923-8365 , White, Ryen W., Pecina, Pavel, Soergel, Dagobert, Huang, Xiaoli and Shafran, Izhak (2007) Overview of the CLEF-2006 cross-language speech retrieval track. In: CLEF 2006: Workshop on Cross-Language Information Retrieval and Evaluation, 20-22 Sept. 2006, Alicante, Spain. (2007)
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3
TREC-2006 at Maryland: Blog, Enterprise, Legal and QA Tracks
In: DTIC (2006)
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4
Comparing User-Assisted and Automatic Query Translation
In: DTIC AND NTIS (2005)
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5
Mandarin-English Information (MEI) : investigating translingual speech retrieval
In: Computer speech and language. - Amsterdam [u.a.] : Elsevier 18 (2004) 2, 163-179
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6
Mandarin-English Information (MEI): investigating translingual speech retrieval
In: Computer speech and language. - Amsterdam [u.a.] : Elsevier 18 (2004) 2, 163-180
OLC Linguistik
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7
Interactive cross-language document selection
In: Information Retrieval Journal. - Dordrecht [u.a.] : Springer Science + Business Media B.V. 7 (2004) 1-2, 205-228
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8
Les dictionnaires électroniques
Zock, Michael (Hrsg.); Carroll, John (Hrsg.); Baldwin, Timothy (Mitarb.)...
In: Traitement automatique des langues. - Saint-Cloud : ATALA 44 (2003) 2, 7-245
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9
Parsing and Tagging of Bilingual Dictionary
In: DTIC (2003)
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10
Parsing and Tagging of Binlingual Dictionary
In: DTIC (2003)
Abstract: Bilingual dictionaries hold great potential as a source of lexical resources for training and testing automated systems for optical character recognition, machine translation, and cross-language information retrieval. In this paper, we describe a system for extracting term lexicons from printed bilingual dictionaries. Our work was divided into three phases - dictionary segmentation, entry tagging, and generation. In segmentation, pages are divided into logical entries based on structural features learned from selected examples. The extracted entries are associated with functional labels and passed to a tagging module which associates linguistic labels with each word or phrase in the entry. The output of the system is a structure that represents the entries from the dictionary. We have used this approach to parse a variety of dictionaries with both Latin and non-Latin alphabets, and demonstrate the results of term lexicon generation for retrieval from a collection of French news stories using English queries. ; The original document contains color images. Additional reports nos. are CS-TR-4529 and UMIACS-TR-2003-97
Keyword: *BILINGUAL DICTIONARIES; *CROSS-LANGUAGE IR; *DICTIONARIES; *ENGLISH LANGUAGE; *LEXICOGRAPHY; *LINGUISTICS; AUTOMATION; Information Science; INTERROGATION; LABELS; Linguistics; LOGICAL ANALYSIS; MACHINE TRANSLATION; OCR; OPTICAL CHARACTER RECOGNITION; OUTPUT; PAGE SEGMENTATION; PARSERS; RESOURCES; SEGMENTED; SOURCES; VOCABULARY
URL: http://www.dtic.mil/docs/citations/ADA452407
http://oai.dtic.mil/oai/oai?&verb=getRecord&metadataPrefix=html&identifier=ADA452407
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11
Comparing User-assisted and Automatic Query Translation
In: DTIC (2003)
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12
Comparing User-assisted and Automatic Query Translation
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13
NTCIR CLIR Experiments at the University of Maryland
In: DTIC (2000)
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14
TREC-8 Experiments at Maryland: CLIR, QA and Routing
In: DTIC (2000)
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