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Back to Basics - Again - for Domain Specific Retrieval. This volume
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In: http://clef.isti.cnr.it/2008/working_notes/Berkeley_Domain_Specific_08.pdf (2008)
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Experiments in Classification Clustering and Thesaurus Expansion for Domain Specific Cross-Language Retrieval
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In: http://www.clef-campaign.org/2007/working_notes/larsonclef2007_ds.pdf
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MIRACLE at VideoCLEF 2008: Classification of Multilingual Speech Transcripts
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In: http://clef.isti.cnr.it/2008/working_notes/Villena2-paperCLEF2008_MIRACLE_Vid2RSS2008.pdf
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Universidad Carlos III de Madrid
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In: http://clef.isti.cnr.it/2009/working_notes/Lana-paperCLEF2009_MIRACLE_ImageCLEFmed2009.pdf
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MIRACLE-GSI at ImageCLEFphoto 2009: Comparing Clustering vs. Classification for Result Reranking
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In: http://clef.isti.cnr.it/2009/working_notes/Villena-paperCLEF2009_MIRACLE_ImageCLEFphoto2009.pdf
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Abstract:
This paper describes the participation of MIRACLE-GSI research consortium at the ImageCLEF 2009 Photo Retrieval Task. For this campaign, the main purpose of our experiments was to compare the performance of a “standard ” clustering algorithm, based on the k-Medoids algorithm, against a more simple classification technique that makes use of the cluster assignment that was provided for a subset of topics by the task organizers. First a common baseline algorithm was used in all experiments to process the document collection: text extraction, tokenization, conversion to lowercase, filtering, stemming and finally, indexing and retrieval. Then this baseline algorithm is combined with these two different result reranking techniques. As expected, results show that any reranking method outperforms a standard non-clustering image search baseline algorithm in terms of cluster recall. In addition, using the information of cluster assignments leads to the best results.
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Keyword:
2009; Categories and Subject Descriptors H.3 [Information Storage and Retrieval; CLEF; domain-specific vocabulary; E.2 [Data Storage Representations]. Keywords Image retrieval; H.2.5 Heterogeneous Databases; H.3.1 Content Analysis and Indexing; H.3.2 Information Storage; H.3.3 Information Search and Retrieval; H.3.4 Systems and Software; H.3.7 Digital libraries. H.2 [Database Management; ImageCLEF; ImageCLEF Photo Retrieval task; indexing; information retrieval; linguistic engineering; relevance feedback; thesaurus; topic expansion
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URL: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.506.7357
http://clef.isti.cnr.it/2009/working_notes/Villena-paperCLEF2009_MIRACLE_ImageCLEFphoto2009.pdf
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MIRACLE-GSI at ImageCLEFphoto 2008: Experiments on Semantic and Statistical Topic Expansion
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In: http://clef.isti.cnr.it/2008/working_notes/Villena1-paperCLEF2008_MIRACLE_ImageCLEFphoto2008.pdf
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MIRACLE at ImageCLEFmed 2008: Evaluating Strategies for Automatic Topic Expansion
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In: http://clef.isti.cnr.it/2008/working_notes/Lana1-paperCLEF2008_MIRACLE_ImageCLEFmed2008.pdf
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