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Survey Paper | Information Technology | Kenya | Volume 6 Issue 12, December 2017 | Popularity: 6.6 / 10

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A Survey of Context-Aware Healthcare Recommender Systems

Mohamed Hussein Abdi, George Onyango Okeyo, Ronald Waweru Mwangi

Abstract: The advent of social web has transformed users from sheer consumers to ardent producers of information. The rapid growth coupled with the reliance on the internet for information ranging from e-commerce, e-government and social networks has led to infobesity. Recommender Systems have become essential tool to aid users to overcome the problem of information overload and provide personalized relevant suggestions. The use of Recommender Systems have been successful in both industry and academia. Recommender systems have also found their way into the Healthcare domain with varied applications. Despite the growing practical demand, a few challenges are hindering the adoption of Recommender Systems in the Healthcare. The purpose of this study is to understand the trend of Recommender Systems applications in Healthcare by examining the published literature, and to provide practitioners and researchers with insight and future direction. We conducted a focused literature review to identify research papers on Recommender Systems in the Healthcare in the last ten years. The key findings of this survey is that the application of Recommender Systems in Healthcare is evolving. The incorporation of contextual information is limited although it has been suggested as a key ingredient to improving the quality of the recommendations and the accuracy of the predications. It is important to point out that aside from the common filtering problems of sparsity, cold start and scalability, a socio-technical issue of privacy, security and trust is emerging. Collaborative Filtering technique is predominantly in use in Healthcare Recommender Systems. Incorporation of contextual information is limited. Privacy, security and trust concerns may hinder the widespread use and acceptance of the Healthcare Recommender Systems.

Keywords: Collaborative Filtering, Context-Aware, Healthcare Recommender Systems, Quality Recommendations, Accurate Predictions, Privacy

Edition: Volume 6 Issue 12, December 2017

Pages: 962 - 967

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