Context: The NASA Aviation Safety Reporting System (ASRS) is a voluntary confidential aviation safety reporting system. The ASRS receives reports from pilots, air traffic controllers, flight attendants and other involved in aviation operations. The reports are de-identified and coded by ASRS expert safety analysts. The de-identified reports are then disseminated to the aviation community in a number of ways including entry into an online database. Augmenting the discovery of topics of user interest in this online database would therefore be beneficial to the community it serves. Aim: We propose and execute an experiment to assess the use of seed term topic modeling using the database narratives to identify UAS reports. The use of seed term topic modeling would enable users to identify groups of related narratives associated to a topic of their interest. Method: We use a newly curated field in ASRS reports which identify UAS from non-UAS reports in combination of different set of UAS related terms to assess if seed topic modeling can be used in ASRS.


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    Titel :

    Assessing the use of UAS-related terms in ASRS using Seed Topic Modeling


    Beteiligte:
    C. Paradis (Autor:in) / M. D. Davies (Autor:in) / B. L. Hooey (Autor:in)

    Erscheinungsdatum :

    2022


    Format / Umfang :

    4 pages


    Medientyp :

    Report


    Format :

    Keine Angabe


    Sprache :

    Englisch




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