Research Reports

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This collection is a subset of the MSI research in which researchers can self-archive the full-text of the work for which they retain the copyrights by depositing to this collection. Please note that some research published in journals cannot be posted on the public MSI collection, instead, MSI provides links to the record's DOI in a publication database available at https://www.msi.umn.edu/reports/

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    Computational Approaches to Measuring the Similarity of Short Contexts : A Review of Applications and Methods
    (University of Minnesota Supercomputing Institute, 2010-10) Pedersen, Ted
    Measuring the similarity of short written contexts is a fundamental problem in Natural Language Processing. This article provides a unifying framework by which short context problems can be categorized both by their intended application and proposed solution. The goal is to show that various problems and methodologies that appear quite different on the surface are in fact very closely related. The axes by which these categorizations are made include the format of the contexts (headed versus headless), the way in which the contexts are to be measured (first-order versus second-order similarity), and the information used to represent the features in the contexts (micro versus macro views). The unifying thread that binds together many short context applications and methods is the fact that similarity decisions must be made between contexts that share few (if any) words in common.
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    UMLS::Similarity: Measuring the Relatedness and Similarity of Biomedical Concepts
    (Association for Computational Linguistics, 2013-06) McInnes, Bridget; Liu, Ying; Pedersen, Ted; Melton, Genevieve; Pakhomov, Serguei
    UMLS::Similarity is freely available open source software that allows a user to measure the semantic similarity or relatedness of biomedical terms found in the Uniļ¬ed Medical Language System (UMLS). It is written in Perl and can be used via a command line interface, an API, or a Web interface.