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NTCIR9-GeoTime Overview - Evaluating Geographic and Temporal Search: Round 2, In this proceedings
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In: http://research.nii.ac.jp/ntcir/workshop/OnlineProceedings9/NTCIR/01-NTCIR9-OV-GEOTIME-GeyF.pdf (2011)
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GeoCLEF 2008: The CLEF 2008 Cross-Language Geographic Information Retrieval Track Overview
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In: http://www.clef-campaign.org/2008/working_notes/GeoCLEF-2008-overview-notebook-paperWNfinal.pdf (2008)
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Berkeley2 at GeoCLEF: Cross-Language Geographic Information Retrieval of German and English Documents
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In: http://www.clef-campaign.org/2005/working_notes/workingnotes2005/gey205.pdf (2005)
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UC Berkeley at CLEF-2003 – Russian language experiments and domain-specific retrieval
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In: http://clef.isti.cnr.it/2003/WN_web/29a.pdf (2004)
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Translingual vocabulary mappings for multilingual information access: SIGIR
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In: http://www.mariapinto.es/ciberabstracts/Articulos/larson.pdf (2002)
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Harvesting Translingual Vocabulary Mappings for Multilingual Digital Libraries
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In: http://cheshire.lib.berkeley.edu/p64-larson.pdf (2002)
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Harvesting Translingual Vocabulary Mappings for Multilingual Digital Libraries
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In: http://metadata.sims.berkeley.edu/GrantSupported/./papers/p64-larson.pdf (2002)
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Abstract:
This paper presents a method of information harvesting and consolidation to support the multilingual information requirements for cross-language information retrieval within digital library systems. We describe a way to create both customized bilingual dictionaries and multilingual query mappings from a source language to many target languages. We will describe a multilingual conceptual mapping resource with broad coverage (over 100 written languages can be supported) that is truly multilingual as opposed to bilingual parings usually derived from machine translation. This resource is derived from the 10+ million title online library catalog of the University of California. It is created statistically via maximum likelihood associations from word and phrases in book titles of many languages to human assigned subject headings in English. The 150,000 subject headings can form interlingua mappings between pairs of languages or from one language to several languages. While our current demonstration prototype maps between ten languages (English, Arabic, Chinese, French, German, Italian, Japanese, Portuguese, Russian, Spanish), extensions to additional languages are straightforward. We also describe how this resource is being expanded for languages where linguistic coverage is limited in our initial database, by automatically harvesting new information from international online library catalogs using the Z39.50 networked library search protocol.
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Keyword:
Categories and Subject Descriptors H.3.3 [Information Search and Retrieval; Design; H.3.7 [Digital Libraries; H.5.2 [User Interfaces; Natural Language General Terms Algorithms; Search process; Systems issues
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URL: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.15.8723 http://metadata.sims.berkeley.edu/GrantSupported/./papers/p64-larson.pdf
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Research to Improve Cross-Language Retrieval { Position Paper for CLEF
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In: http://metadata.sims.berkeley.edu/GrantSupported/./papers/clef-position-paper.ps (2001)
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Translation Term Weighting and Combining Translation Resources in Cross-Language Retrieval
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In: http://trec.nist.gov/pubs/trec10/papers/berkeley_trec10.pdf (2001)
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English-Chinese Cross-Language IR using Bilingual Dictionaries
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In: http://metadata.sims.berkeley.edu/GrantSupported/./papers/trec9.pdf (2001)
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English-chinese cross-language ir using bilingual dictionaries
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In: http://ucdata.berkeley.edu/personal/fred/my-papers/trec9_berkeley.pdf (2001)
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English-chinese cross-language ir using bilingual dictionaries
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In: http://trec.nist.gov/pubs/trec9/papers/trec9_berkeley.pdf (2001)
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English-Chinese Cross-Language IR using Bilingual Dictionaries
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In: http://trec.nist.gov/pubs/trec9/./papers/trec9_berkeley.ps (2001)
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English-German Cross-Language Retrieval for the GIRT Collection -- Exploiting a Multilingual Thesaurus
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In: http://trec.nist.gov/pubs/trec8/./papers/Berkeley-GIRT-trec8.ps (1999)
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1. NTCIR Cross-Language Retrieval
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In: http://www.lrec-conf.org/proceedings/lrec2008/pdf/363_paper.pdf
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Applying Text Categorization to Vocabulary Enhancement for Japanese-English Cross-Language Retrieval
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In: http://ucdata.berkeley.edu/personal/fred/my-papers/singapore.pdf
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1. NTCIR Cross-Language Retrieval
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In: http://www.mt-archive.info/LREC-2008-Gey.pdf
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General Terms
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In: http://www.dcs.gla.ac.uk/~hideo/pub/geoclef05/geoclef2005overview.pdf
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Xie: GeoCLEF 2007: the CLEF 2007 Cross-Language Geographic Infor¬ma¬tion Retrie¬val Track Overview
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In: http://www.clef-campaign.org/2007/working_notes/mandlCLEF2007_Geo_Overview.pdf
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Xie: GeoCLEF 2007: the CLEF 2007 Cross-Language Geographic Infor¬ma¬tion Retrie¬val Track Overview
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In: http://www.linguateca.pt/Diana/download/MandletalGeoCLEF2007WN.pdf
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