Domain knowledge acquisition by automatic semantic annotating and pattern mining

Tianyong Hao, Yingying Qu, Fang Xia

    Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review

    3 Citations (Scopus)

    Abstract

    Manual knowledge acquisition is extremely laborious and time consuming. In this paper, we propose a new automatic method for domain knowledge acquisition by semantic annotating and pattern mining. This method makes use of Minipar to label sentences and extract structural patterns. Semantic bank is proposed to annotate and represent concepts with semantic labels considering sentence context. The method can further learn and assign relations to previously extracted concepts by pattern matching. The involved concepts and semantic labels with learned relations together construct a domain knowledge base. Preliminary experiments on Yahoo! Data in "heart diseases" category show that this method is feasible for automatic domain knowledge acquisition. © 2012 IEEE.
    Original languageEnglish
    Title of host publicationProceedings - 2012 International Conference on Information Retrieval and Knowledge Management, CAMP'12
    Pages34-38
    DOIs
    Publication statusPublished - 2012
    Event2012 International Conference on Information Retrieval and Knowledge Management, CAMP'12 - Kuala Lumpur, Malaysia
    Duration: 13 Mar 201215 Mar 2012

    Conference

    Conference2012 International Conference on Information Retrieval and Knowledge Management, CAMP'12
    Country/TerritoryMalaysia
    CityKuala Lumpur
    Period13/03/1215/03/12

    Research Keywords

    • knowledge acqistion
    • semantic annotation
    • semantic bank
    • structural pattern
    • transform rule

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