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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
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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
Abstract: In this paper we will briefly describe the approaches taken by Berkeley for the main GeoCLEF 2008 tasks (Mono and Bilingual retrieval). The approach this year used probabilistic text retrieval based on logistic regression and incorporating blind rele-vance feedback for all of the runs and in addition we ran a number of tests combining this type of search with OKAPI BM25 searches using a fusion approach. All transla-tion for bilingual tasks was performed using the LEC Power Translator PC-based MT system. Our results were good overall with Cheshire systems runs appearing in the top 5 participants for each task (German, English and Portuguese both Monolingual and Bilingual) with the highest ranked runs for Monolingual Portuguese and for Bilin-gual German, English and Portuguese. All of these top-ranked runs used the fusion approach. However, once again this year we did not attempt to do any specialized geographic processing, because it appears that purely textual approaches to GIR are more effective when only textual topics, lacking explicit geographic coordinate constraints, are used.
Keyword: Categories and Subject Descriptors H.3 [Information Storage and Retrieval; H.3.1 Content Analysis and Indexing; H.3.3 Infor- mation Search and Retrieval General Terms Algorithms; Logistic Regression; Measurement Keywords Cheshire II; Performance
URL: http://clef.isti.cnr.it/2008/working_notes/larson_GeoCLEF.pdf
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.533.3693
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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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