Impacts of Subjective Aspects in the Matching of Dentists and Patients in Dental Care Recommendation Systems

Publisher:
AISEL
Publication Type:
Conference Proceeding
Citation:
AISEL proceedings of International Conference on Information Systems (ICIS), 2016, pp. 1 - 19
Issue Date:
2016-12-14
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ICIS_Paper ID 0957 2016 _ Dental Care Recommendation Systems_revised_FINAL.pdfPublished version1.02 MB
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The recent growth of social media has impacted the way users are searching and sharing health information. Online review and rating websites, in particular, provide a support for patients to share their opinions. Yet, finding the right information can be a challenge, particularly when there is no consistency in the evaluation criteria across various sources. The invasive nature of many dental treatments highlights the importance of selecting a suitable trustworthy provider for dental patients. This study proposes a new trust-enhanced information model in which dentists and patients are profiled based on subjective information. Subjective aspects of dentists are extracted from dental crowd sources such as DrOogle and Yelp. Two matching algorithms are presented. They are based on 580 responses to an online survey. The subjective aspects of both patients and dentists are important factors which are incorporated to improve the matching capability of dental care recommendation systems.
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