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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Page: 1...13 14 15 16 17 Hits 321 – 329 of 329 321 General Terms Kula Kekeba Tune; Vasudeva Varma In: http://www.clef-campaign.org/2007/working_notes/kulaclef2007.pdf BASE Show details 322 Combining Probabilistic and Translation-Based Models for Information Retrieval based on Word Sense Annotations Elisabeth Wolf; Delphine Bernhard; Iryna Gurevych In: http://elara.tk.informatik.tu-darmstadt.de/publications/2009/wolf-paperCLEF2009.pdf BASE Show details 323 Cheshire at GeoCLEF 2007: Retesting Text Retrieval Baselines Ray R. Larson In: http://www.clef-campaign.org/2007/working_notes/larsonclef2007geo.pdf BASE Show details 324 Cross-lingual Information Retrieval with Explicit Semantic Analysis Philipp Sorg In: http://www.aifb.uni-karlsruhe.de/WBS/pso/publications/sorg_paperCLEF2008.pdf Abstract: We have participated on the monolingual and bilingual CLEF Ad-Hoc Retrieval Tasks, using a novel extension of the by now well-known Explicit Semantic Analysis (ESA) approach. We call this extension Cross-Language Explicit Semantic Analysis (CL-ESA) as it allows to apply ESA in a cross-lingual information retrieval setting. In essence, ESA represents documents as vectors in the space of Wikipedia articles, using the tfidf measure to capture how “important ” a Wikipedia article is for a specific word. The interesting property of ESA is that arbitrary documents can be represented as a vector with respect to the Wikipedia article space. ESA thus replaces the standard BOW model for retrieval. In our cross-lingual extension of ESA, the cross-language links of Wikipedia are used in order to map the ESA vectors between different languages, thus allowing retrieval across languages. Our results are far behind the ones of other systems on the monolingual and ad-hoc retrieval tasks, but our motivation was to find out the potential of the CL-ESA approach using a first and unoptimized implementation thereof. Keyword: Experimentation Keywords Cross-language Information Retrieval; Explicit Semantic Analysis; Measurement; Performance; Wikipedia URL: http://www.aifb.uni-karlsruhe.de/WBS/pso/publications/sorg_paperCLEF2008.pdf http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.140.7270 BASE Hide details 325 University of Hagen at GeoCLEF 2008: Combining IR and QA for Geographic Information Retrieval Johannes Leveling; Sven Hartrumpf In: http://www.clef-campaign.org/2008/working_notes/leveling-paperCLEF2008.pdf BASE Show details 326 DCU and UTA at ImageCLEFPhoto 2007 Anni Järvelin; Peter Wilkins; Tomasz Adamek... In: http://www.clef-campaign.org/2007/working_notes/JarvelinCLEF2007.pdf BASE Show details 327 OPTIMISING THE EMAIL KNOWLEDGE EXTRACTION SYSTEM TO SUPPORT KNOWLEDGE WORK In: http://is2.lse.ac.uk/asp/aspecis/20070167.pdf BASE Show details 328 Using IR-n for Information retrieval of Genomics Track María Pardiño; Rafael M. Terol; Patricio Martínez-barco... In: http://trec.nist.gov/pubs/trec16/papers/ualicante.geo.final.pdf BASE Show details 329 Prompt and Rater Effects in Second Language Writing Performance Assessment. Lim, Gad S. BASE Show details Page: 1...13 14 15 16 17

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