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1
Berkeley at NTCIR-2: Chinese, Japanese, and English IR Experiments
In: http://metadata.sims.berkeley.edu/GrantSupported/./papers/ntcir2001.pdf (2001)
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2
English-Chinese Cross-Language IR using Bilingual Dictionaries
In: http://metadata.sims.berkeley.edu/GrantSupported/./papers/trec9.pdf (2001)
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3
English-chinese cross-language ir using bilingual dictionaries
In: http://trec.nist.gov/pubs/trec9/papers/trec9_berkeley.ps (2001)
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4
English-chinese cross-language ir using bilingual dictionaries
In: http://ucdata.berkeley.edu/personal/fred/my-papers/trec9_berkeley.pdf (2001)
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5
English-chinese cross-language ir using bilingual dictionaries
In: http://trec.nist.gov/pubs/trec9/papers/trec9_berkeley.pdf (2001)
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6
English-Chinese Cross-Language IR using Bilingual Dictionaries
In: http://trec.nist.gov/pubs/trec9/./papers/trec9_berkeley.ps (2001)
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7
Automatic Construction of a Japanese-English Lexicon and its Application in Cross-Language Information Retrieval
In: http://www.clis.umd.edu/conferences/midas/papers/chen.ps (1999)
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8
English-German Cross-Language Retrieval for the GIRT Collection - Exploiting a Multilingual Thesaurus
In: http://trec.nist.gov/pubs/trec8/papers/Berkeley-GIRT-trec8.pdf (1999)
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9
English-German Cross-Language Retrieval for the GIRT Collection -- Exploiting a Multilingual Thesaurus
In: http://trec.nist.gov/pubs/trec8/./papers/Berkeley-GIRT-trec8.ps (1999)
Abstract: For TREC-8, the Berkeley experiments concentrated on the special GIRT collection. We utilized the GIRT thesaurus in multiple ways in working on EnglishGerman Cross-Language IR. Since the GIRT collection is truly multilingual (documents contain both German and English text), one would expect multilingual queries to achieve the best performance. This proved not to be the case. 1 Introduction Successful cross-language information retrieval (CLIR) combines linguistic techniques (phrase discovery, machine translation, bilingual dictionary lookup) with robust monolingual information retrieval. The Berkeley group has been using the technique of logistic regression from the beginning of the TREC series of conferences. In TREC-2 [2] we derived a statistical formula for predicting probability of relevance based upon statistical clues contained with documents, queries and collections as a whole. This formula was used for document retrieval in Chinese[3] and Spanish in TREC-4 through TREC-6.
URL: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.38.7064
http://trec.nist.gov/pubs/trec8/./papers/Berkeley-GIRT-trec8.ps
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10
Manual Queries and Machine Translation in Cross-language Retrieval and Interactive Retrieval with Cheshire II at TREC-7
In: http://trec.nist.gov/pubs/trec7/papers/berkeley.trec7.ps (1998)
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11
Berkeley at NTCIR-2: Chinese, Japanese, and English IR Experiments
In: http://research.nii.ac.jp/ntcir/workshop/OnlineProceedings2/ntcir2_berkeley.pdf
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12
Applying Text Categorization to Vocabulary Enhancement for Japanese-English Cross-Language Retrieval
In: http://ucdata.berkeley.edu/personal/fred/my-papers/singapore.pdf
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13
Manual Queries and Machine Translation in Cross-language Retrieval and Interactive Retrieval
In: http://trec.nist.gov/pubs/trec7/papers/berkeley.trec7.pdf.gz
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