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KARE: a hybrid reasoning approach for promoting active lifestyle
Citation
Ali, R and Siddiqi, MH and Lee, S and Kang, BH, KARE: a hybrid reasoning approach for promoting active lifestyle, Proceedings of the ACM IMCOM 2015, 8-10 January, Bali, Indonesia, pp. 1-5. ISBN 978-1-4503-3377-1 (2015) [Refereed Conference Paper]
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Copyright Statement
Copyright 2015 ACM
Official URL: http://dl.acm.org/citation.cfm?id=2701126&CFID=651...
DOI: doi:10.1145/2701126.2701156
Abstract
Healthcare systems provide suitable services in different domains to help people in fitting themselves into their best pattern of life. This study is focused on the development of a hybrid reasoning engine called KARE (knowledge acquisition and reasoning engine) which is the core reasoning module of ATHENA (activity-awareness for human-engaged wellness applications) platform, carried out at UCLab as a project for promoting active lifestyle. This engine recommends food, mental and physical therapy to the ATHENA users that are based on their personal preferences, historical physical, mental and social health information. In KARE, a hybrid approach is used for reasoning which internally combines the predictions of multiple parallel reasoners into a collective decision. Random Forest, Naïve Bayes and IB1 algorithms are used in parallel in each of the reasoner to generate personalized recommendations for the specified service. The predictions of all the individual reasoners are combined using majority voting scheme to enhance the predictive accuracy of the individual reasoner. The proposed hybrid reasoning approach is tested on real world dataset of weight management, collected under the ATHENA project. The accuracy of correct recommendations for food, physical and mental therapies is 98.7%
Item Details
| Item Type: | Refereed Conference Paper |
|---|---|
| Keywords: | reasoning, hybrid reasoning, learning, KARE, healthcare, recommendations, active lifestyle |
| Research Division: | Information and Computing Sciences |
| Research Group: | Artificial Intelligence and Image Processing |
| Research Field: | Artificial Intelligence and Image Processing not elsewhere classified |
| Objective Division: | Information and Communication Services |
| Objective Group: | Information Services |
| Objective Field: | Information Services not elsewhere classified |
| UTAS Author: | Kang, BH (Professor Byeong Kang) |
| ID Code: | 107240 |
| Year Published: | 2015 |
| Web of Science® Times Cited: | 1 |
| Deposited By: | Information and Communication Technology |
| Deposited On: | 2016-03-08 |
| Last Modified: | 2017-11-13 |
| Downloads: | 0 |
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