The Experts below are selected from a list of 129612 Experts worldwide ranked by ideXlab platform
Udo Hahn - One of the best experts on this subject based on the ideXlab platform.
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MIE - Cross-lingual alignment of biomedical acronyms and their expansions.
Studies in health technology and informatics, 2006Co-Authors: Kornél G. Markó, Philipp Daumke, Udo HahnAbstract:We propose a method that aligns biomedical acronyms and their definitions across different languages. The approach is based upon a freely available tool for the extraction of abbreviations together with their expansions, and the subsequent normalization of language-specific variants, synonyms, and translations of the extracted acronym definitions. In this step, acronym expansions are mapped onto a language-Independent Concept-layer on which intra- as well as interlingual comparisons are drawn.
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morphosaurus design and evaluation of an interlingua based cross language document retrieval engine for the medical domain
Methods of Information in Medicine, 2005Co-Authors: K Marko, Stefan Schulz, Udo HahnAbstract:approach to account for the particular challenges that arise in the design and implementation of crosslanguage document retrieval systems for the medical domain. Methods: Documents, as well as queries, are mapped to a language-Independent Conceptual layer on which retrieval operations are performed. We contrast this approach with the direct translation of German queries to English ones which, subsequently, are matched against English documents. Results: We evaluate both approaches, interlinguabased and direct translation, on a large medical document collection, the OHSUMED corpus. A substantial benefit for interlingua-based document retrieval using German queries on English texts is found, which amounts to 93% of the (monolingual) English baseline. Conclusions: Most state-of-the-art cross-language information retrieval systems translate user queries to the language(s) of the target documents. In contradistinction to this approach, translating both documents and user queries into a language-Independent, Concept-like representation format is more beneficial to enhance cross-language retrieval performance
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RIAO - Crossing languages in text retrieval via an interlingua
2004Co-Authors: Udo Hahn, Stefan Schulz, Kornél G. Markó, Michael Poprat, Joachim Wermter, Percy NohamaAbstract:We introduce an interlingua-based approach to cross-language information retrieval, in which queries, as well as documents, are mapped onto a language-Independent Concept layer on which retrieval operations are performed. This approach is contrasted with one which directly translates non-English queries (German and Portuguese, in our experiments) to English ones which, subsequently, are processed on English documents. We report on the empirical evaluation of both approaches on a large medical document collection (the Ohsumed corpus).
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FLAIRS Conference - An Experimental Assessment of Direct Versus. Interlingual Translation for Cross-Language Information Retrieval.
2004Co-Authors: Michael Poprat, Udo Hahn, Stefan Schulz, Joachim Wermter, Kornél G. MarkóAbstract:We introduce an interlingua-based approach to crosslanguage information retrieval, in which queries, as well as documents, are mapped onto a language-Independent Concept layer and retrieval operations are performed at the level of that interlingua. This approach is contrasted with one which operates without such an intermediary Concept level. Non-English queries (German ones, in our experiments) are directly translated to English queries which, subsequently, are processed on English documents. We provide an empirical evaluation of both alternatives on a large medical document collection.
Alessandro Raganato - One of the best experts on this subject based on the ideXlab platform.
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sew embed at semeval 2017 task 2 language Independent Concept representations from a semantically enriched wikipedia
Meeting of the Association for Computational Linguistics, 2017Co-Authors: Claudio Delli Bovi, Alessandro RaganatoAbstract:This paper describes Sew-Embed, our language-Independent approach to multilingual and cross-lingual semantic word similarity as part of the SemEval-2017 Task 2. We leverage the Wikipedia-based Concept representations developed by Raganato et al. (2016), and propose an embedded augmentation of their explicit high-dimensional vectors, which we obtain by plugging in an arbitrary word (or sense) embedding representation, and computing a weighted average in the continuous vector space. We evaluate Sew-Embed with two different off-the-shelf embedding representations, and report their performances across all monolingual and cross-lingual benchmarks available for the task. Despite its simplicity, especially compared with supervised or overly tuned approaches, Sew-Embed achieves competitive results in the cross-lingual setting (3rd best result in the global ranking of subtask 2, score 0.56).
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SemEval@ACL - Sew-Embed at SemEval-2017 Task 2: Language-Independent Concept Representations from a Semantically Enriched Wikipedia
Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017), 2017Co-Authors: Claudio Delli Bovi, Alessandro RaganatoAbstract:This paper describes Sew-Embed, our language-Independent approach to multilingual and cross-lingual semantic word similarity as part of the SemEval-2017 Task 2. We leverage the Wikipedia-based Concept representations developed by Raganato et al. (2016), and propose an embedded augmentation of their explicit high-dimensional vectors, which we obtain by plugging in an arbitrary word (or sense) embedding representation, and computing a weighted average in the continuous vector space. We evaluate Sew-Embed with two different off-the-shelf embedding representations, and report their performances across all monolingual and cross-lingual benchmarks available for the task. Despite its simplicity, especially compared with supervised or overly tuned approaches, Sew-Embed achieves competitive results in the cross-lingual setting (3rd best result in the global ranking of subtask 2, score 0.56).
Stefan Schulz - One of the best experts on this subject based on the ideXlab platform.
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morphosaurus design and evaluation of an interlingua based cross language document retrieval engine for the medical domain
Methods of Information in Medicine, 2005Co-Authors: K Marko, Stefan Schulz, Udo HahnAbstract:approach to account for the particular challenges that arise in the design and implementation of crosslanguage document retrieval systems for the medical domain. Methods: Documents, as well as queries, are mapped to a language-Independent Conceptual layer on which retrieval operations are performed. We contrast this approach with the direct translation of German queries to English ones which, subsequently, are matched against English documents. Results: We evaluate both approaches, interlinguabased and direct translation, on a large medical document collection, the OHSUMED corpus. A substantial benefit for interlingua-based document retrieval using German queries on English texts is found, which amounts to 93% of the (monolingual) English baseline. Conclusions: Most state-of-the-art cross-language information retrieval systems translate user queries to the language(s) of the target documents. In contradistinction to this approach, translating both documents and user queries into a language-Independent, Concept-like representation format is more beneficial to enhance cross-language retrieval performance
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RIAO - Crossing languages in text retrieval via an interlingua
2004Co-Authors: Udo Hahn, Stefan Schulz, Kornél G. Markó, Michael Poprat, Joachim Wermter, Percy NohamaAbstract:We introduce an interlingua-based approach to cross-language information retrieval, in which queries, as well as documents, are mapped onto a language-Independent Concept layer on which retrieval operations are performed. This approach is contrasted with one which directly translates non-English queries (German and Portuguese, in our experiments) to English ones which, subsequently, are processed on English documents. We report on the empirical evaluation of both approaches on a large medical document collection (the Ohsumed corpus).
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FLAIRS Conference - An Experimental Assessment of Direct Versus. Interlingual Translation for Cross-Language Information Retrieval.
2004Co-Authors: Michael Poprat, Udo Hahn, Stefan Schulz, Joachim Wermter, Kornél G. MarkóAbstract:We introduce an interlingua-based approach to crosslanguage information retrieval, in which queries, as well as documents, are mapped onto a language-Independent Concept layer and retrieval operations are performed at the level of that interlingua. This approach is contrasted with one which operates without such an intermediary Concept level. Non-English queries (German ones, in our experiments) are directly translated to English queries which, subsequently, are processed on English documents. We provide an empirical evaluation of both alternatives on a large medical document collection.
K Marko - One of the best experts on this subject based on the ideXlab platform.
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morphosaurus design and evaluation of an interlingua based cross language document retrieval engine for the medical domain
Methods of Information in Medicine, 2005Co-Authors: K Marko, Stefan Schulz, Udo HahnAbstract:approach to account for the particular challenges that arise in the design and implementation of crosslanguage document retrieval systems for the medical domain. Methods: Documents, as well as queries, are mapped to a language-Independent Conceptual layer on which retrieval operations are performed. We contrast this approach with the direct translation of German queries to English ones which, subsequently, are matched against English documents. Results: We evaluate both approaches, interlinguabased and direct translation, on a large medical document collection, the OHSUMED corpus. A substantial benefit for interlingua-based document retrieval using German queries on English texts is found, which amounts to 93% of the (monolingual) English baseline. Conclusions: Most state-of-the-art cross-language information retrieval systems translate user queries to the language(s) of the target documents. In contradistinction to this approach, translating both documents and user queries into a language-Independent, Concept-like representation format is more beneficial to enhance cross-language retrieval performance
Claudio Delli Bovi - One of the best experts on this subject based on the ideXlab platform.
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SemEval@ACL - Sew-Embed at SemEval-2017 Task 2: Language-Independent Concept Representations from a Semantically Enriched Wikipedia
Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017), 2017Co-Authors: Claudio Delli Bovi, Alessandro RaganatoAbstract:This paper describes Sew-Embed, our language-Independent approach to multilingual and cross-lingual semantic word similarity as part of the SemEval-2017 Task 2. We leverage the Wikipedia-based Concept representations developed by Raganato et al. (2016), and propose an embedded augmentation of their explicit high-dimensional vectors, which we obtain by plugging in an arbitrary word (or sense) embedding representation, and computing a weighted average in the continuous vector space. We evaluate Sew-Embed with two different off-the-shelf embedding representations, and report their performances across all monolingual and cross-lingual benchmarks available for the task. Despite its simplicity, especially compared with supervised or overly tuned approaches, Sew-Embed achieves competitive results in the cross-lingual setting (3rd best result in the global ranking of subtask 2, score 0.56).
