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    Neural Network Algorithms for Ontology Informed Information Extraction

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    Author
    Xu, Dongfang
    Issue Date
    2021
    Keywords
    Biomedical Concept Normalization
    Information Extraction
    Neural Network
    Ontology
    Time Normalization
    Advisor
    Bethard, Steven
    
    Metadata
    Show full item record
    Publisher
    The University of Arizona.
    Rights
    Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction, presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
    Abstract
    Ontology, as a formal and explicit specification of a shared conceptualization for a particular domain, is useful in information extraction. On the one hand, since information extraction is concerned with retrieving information for a particular domain, formally and explicitly specifying the concepts of that domain through an ontology defines the boundary of what information needs to be extracted. On the other hand, an ontology, typically consisting of classes (or concepts), attributes (or properties), and relationships (or relations among class members), contains the structured information that information extraction systems aim to extract. In this thesis, we are interested in how using an ontology can improve the information extraction process. We explore two research directions that both employ ontologies in the information extraction process, temporal normalization and biomedical concept normalization. In both research directions, we show that leveraging resources in ontologies helps to build high-performance information extraction systems, and presenting the extracted output using such ontologies makes the structured information concise and interchangeable.
    Type
    text
    Electronic Dissertation
    Degree Name
    Ph.D.
    Degree Level
    doctoral
    Degree Program
    Graduate College
    Information
    Degree Grantor
    University of Arizona
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