| Semantic relation mining of solid compounds in medical corpora. | |
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MedLine Citation:
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PMID: 18487734 Owner: NLM Status: MEDLINE |
Abstract/OtherAbstract:
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In the context of scientific and technical texts, meaning is usually embedded in noun compounds and the semantic interpretation of these compounds deals with the detection and semantic classification of the relation that holds between the compound's constituents. Semantic relation mining, the technology applied for marking up, interpreting, extracting and classifying relations that hold between pairs of words, is an important enterprise that contribute to deeper means of enhancing document understanding technologies, such as Information Extraction, Question Answering, Summarization, Paraphrasing, Ontology Building and Textual Entailment. This paper explores the application of assigning semantic descriptors taken from a multilingual medical thesaurus to a large sample of solid (closed form) compounds taken from large Swedish medical corpora, and determining the relation(s) that may hold between the compound constituents. Our work is inspired by previous research in the area of using lexical hierarchies for identifying relations between two-word noun compounds in the medical domain. In contrast to previous research, Swedish, as other Germanic languages, require further means of analysis, since compounds are written as one sequence with no white space between the words, e.g. virus diseases vs. virussjukdomar, which makes the problem more challenging, since solid compounds are harder to identify and segment. |
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Authors:
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Dimitrios Kokkinakis |
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Publication Detail:
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Type: Journal Article |
Journal Detail:
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Title: Studies in health technology and informatics Volume: 136 ISSN: 0926-9630 ISO Abbreviation: Stud Health Technol Inform Publication Date: 2008 |
Date Detail:
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Created Date: 2008-05-19 Completed Date: 2008-09-30 Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 9214582 Medline TA: Stud Health Technol Inform Country: Netherlands |
Other Details:
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Languages: eng Pagination: 217-22 Citation Subset: T |
Affiliation:
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Department of Swedish Language, Språkdata, University of Gothenburg, Sweden. |
Export Citation:
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| MeSH Terms | |
Descriptor/Qualifier:
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Abstracting and Indexing as Topic Databases, Bibliographic* Decision Support Systems, Clinical* Humans Internet* Medical Subject Headings Multilingualism Natural Language Processing* Semantics* Software Sweden Unified Medical Language System Vocabulary, Controlled* |
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