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A Participatory Model for Multi-Document Health Information Summarisation
Author(s) -
Dinithi Nallaperuma,
Daswin De Silva
Publication year - 2017
Publication title -
ajis. australasian journal of information systems/ajis. australian journal of information systems/australian journal of information systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.351
H-Index - 18
eISSN - 1326-2238
pISSN - 1039-7841
DOI - 10.3127/ajis.v21i0.1393
Subject(s) - relevance (law) , computer science , citizen journalism , process (computing) , key (lock) , participatory sensing , domain (mathematical analysis) , health care , knowledge management , health information , data science , information retrieval , world wide web , political science , computer security , mathematical analysis , mathematics , law , operating system
Increasing availability and access to health information has been a paradigm shift in healthcare provision as it empowers both patients and practitioners alike. Besides awareness, significant time savings and process efficiencies can be achieved through effective summarisation of healthcare information. Relevance and accuracy are key concerns when generating summaries for such documents. Despite advances in automated summarisation approaches, the role of participation has not been explored. In this paper, we propose a new model for multi-document health information summarisation that takes into account the role of participation. The updated IS user participation theory was extended to explicate these roles. The proposed model integrates both extractive and abstractive summarisation processes with continuous participatory inputs to each phase. The model was implemented as a client-server application and evaluated by both domain experts and health information consumers. Results from the evaluation phase indicates the model is successful in generating relevant and accurate summaries for diverse audiences

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