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1
Back to Basics - Again - for Domain Specific Retrieval. This volume
In: http://clef.isti.cnr.it/2008/working_notes/Berkeley_Domain_Specific_08.pdf (2008)
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2
Translating Dialects in Search: Mapping between Specialized Languages of Discourse and Documentary Languages
In: http://people.ischool.berkeley.edu/~vivienp/diss/vpetras-dissertation2006-shortformat.pdf (2006)
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3
Translingual vocabulary mappings for multilingual information access: SIGIR
In: http://www.mariapinto.es/ciberabstracts/Articulos/larson.pdf (2002)
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4
Harvesting Translingual Vocabulary Mappings for Multilingual Digital Libraries
In: http://cheshire.lib.berkeley.edu/p64-larson.pdf (2002)
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5
Harvesting Translingual Vocabulary Mappings for Multilingual Digital Libraries
In: http://metadata.sims.berkeley.edu/GrantSupported/./papers/p64-larson.pdf (2002)
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6
hsql database engine home page. http://hsqldb.sourceforge.net
In: http://www.clef-campaign.org/2005/working_notes/workingnotes2005/larson205.pdf (2001)
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7
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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8
Experiments in Classification Clustering and Thesaurus Expansion for Domain Specific Cross-Language Retrieval
In: http://www.clef-campaign.org/2007/working_notes/larsonclef2007_ds.pdf
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9
Multilingual Query Expansion for CLEF Adhoc-TEL
In: http://clef.isti.cnr.it/2009/working_notes/larson-Adhoc-TEL-CLEF2009.pdf
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10
Domain Specic Retrieval: Back to Basics
In: http://clef.isti.cnr.it/2006/working_notes/workingnotes2006/larson-DSCLEF2006.pdf
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11
Blind Relevance Feedback for the ImageCLEF Wikipedia Retrieval Task
In: http://clef2010.org/resources/proceedings/clef2010labs_submission_72.pdf
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12
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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13
Linked Relevance Feedback for the ImageCLEF Photo Task
In: http://www.clef-campaign.org/2007/working_notes/LarsonCLEF2007_Image.pdf
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14
Probabilistic Text Retrieval for NTCIR9 GeoTime
In: http://research.nii.ac.jp/ntcir/workshop/OnlineProceedings9/NTCIR/05-NTCIR9-GEOTIME-LarsonR.pdf
Abstract: For the NTCIR-9 Workshop UC Berkeley participated only in the GeoTime track. For our initial experiments we used only the Logistic Regression ranking with blind feedback approach that we also used in NTCIR-8. We participated in both English and Japanese monolingual and bilingual search tasks. For all Japanese topics we preprocessed the text using the ChaSen morphological analyzer for term segmentation. For these submitted runs we did not do any special purpose geographic or temporal processing. This brief paper describes the submitted runs and the methods used for them.
Keyword: Logistic Regression; Probabilistic Retrieval
URL: http://research.nii.ac.jp/ntcir/workshop/OnlineProceedings9/NTCIR/05-NTCIR9-GEOTIME-LarsonR.pdf
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.407.6519
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15
Logistic Regression for Metadata: Cheshire takes on Adhoc-TEL
In: http://clef.isti.cnr.it/2008/working_notes/larson_Adhoc_TEL.pdf
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16
Cheshire at GeoCLEF 2008: Text and Fusion Approaches for
In: http://clef.isti.cnr.it/2008/working_notes/larson_GeoCLEF.pdf
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17
Cheshire at GeoCLEF 2007: Retesting Text Retrieval Baselines
In: http://www.clef-campaign.org/2007/working_notes/larsonclef2007geo.pdf
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