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Foreign language peace of mind: a positive emotion drawn from the Chinese EFL learning context
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Succession in Chinese family-SMEs: a gendered analysis of successor learning and development
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Learning to read in Chinese: Evidence for reciprocal relationships between word reading and oral language skills
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Measurement of the muon reconstruction performance of the ATLAS detector using 2011 and 2012 LHC proton-proton collision data.
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In: Symplectic Elements at Oxford ; Europe PubMed Central ; PubMed (http://www.ncbi.nlm.nih.gov/pubmed/) ; Web of Science (Lite) (http://apps.webofknowledge.com/summary.do) ; Scopus (http://www.scopus.com/home.url) ; CrossRef (2014)
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SemEQUAL: Multilingual Semantic Matching in Relational Systems
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Abstract:
In an increasingly multilingual world, it is critical that information management tools organically support the simultaneous use of multiple natural languages.A pre-requisite for efficiently achieving this goal is that the underlying database engines must provide seamless matching of text data across languages. We propose here SemEQUAL, a new SQL functionality for semantic matching of multilingual attribute data. Our current implementation defines matches based on the standard WordNet linguistic ontologies. A performance evaluation of SemEQUAL, implemented using standard SQL:1999 features on a suite of commercial database systems indicates unacceptably slow response times. However, by tuning the schema and index choices to match typical linguistic features, we show that the performance can be improved to a level commensurate with online user interaction.
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Keyword:
Computer Science & Automation (Formerly; School of Automation); Supercomputer Education & Research Centre
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URL: http://eprints.iisc.ernet.in/9846/ http://eprints.iisc.ernet.in/9846/1/SemEQUAL_Feb15th.pdf
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