Keyphrase extraction: from distributional feature engineering to distributed semantic composition

Rui Wang

    Research output: ThesisDoctoral Thesis

    415 Downloads (Pure)

    Abstract

    Automatic Keyphrase Extraction is the fundamental step underpinning many Natural Language Processing tasks. However,
    the performance of the current solutions heavily relies on the selection of features, rendering the algorithms to be dataset
    dependent and failing to capture the semantic meanings of phrases and documents. This research investigated extensively on
    the current solutions and built on the most recent success of deep neural networks in natural language processing to mimic the
    human cognitive process of keyphrase identification. A number of novel models to learn the meaning of phrases and documents
    have been developed and evaluated, achieving the state-of-the-art performance.
    Original languageEnglish
    QualificationDoctor of Philosophy
    Awarding Institution
    • The University of Western Australia
    Supervisors/Advisors
    • Liu, Wei, Supervisor
    • McDonald, Chris, Supervisor
    Thesis sponsors
    Award date9 Jan 2018
    DOIs
    Publication statusUnpublished - 2017

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