The Canonical Model of Structure for Data Extraction in Systematic Reviews of Scientific Research Articles

Bello Aliyu Muhammad, Rahat Iqbal, Anne James

    Research output: Chapter in Book/Report/Conference proceedingConference proceedingpeer-review

    3 Citations (Scopus)

    Abstract

    The systematic review activity is time-consuming, error prone and labour intensive activity due to the manual processes involved; with data extraction being an extremely difficult and cognitively demanding process. Automation can save a significant amount of time and reduces the workload. However, there is no unified approach for automatic data extraction in systematic reviews. This paper presents a canonical model of structure of the papers that serves as a unified approach and a foundation for subsequent extraction of information from scientific research articles automatically. The model was developed using text mining and natural language processing techniques on one thousand (1000) published research papers. A novel approach was used to identify the various section headings from the papers. This approach achieved an accuracy of 82%. A statistical analysis of the most frequent words/phrases in the section headings was used to build the canonical model of structure of the papers.
    Original languageEnglish
    Title of host publication2018 Fifth International Conference on Social Networks Analysis, Management and Security (SNAMS)
    PublisherIEEE Computer Society
    Pages264 - 271
    Number of pages8
    ISBN (Electronic)978-1-5386-9588-3
    ISBN (Print)978-1-5386-9589-0
    DOIs
    Publication statusPublished - 3 Dec 2018
    EventFifth International Conference on Social Networks Analysis, Management and Security - Valencia, Spain
    Duration: 15 Oct 201818 Oct 2018
    Conference number: 5th
    http://emergingtechnet.org/SNAMS2018/

    Conference

    ConferenceFifth International Conference on Social Networks Analysis, Management and Security
    Abbreviated titleSNAMS 2018
    CountrySpain
    CityValencia
    Period15/10/1818/10/18
    Internet address

    Keywords

    • Data extraction
    • Systematic review
    • canonical structure
    • text mining and natural language processing

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