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Information Resources Management Association
Advancing the Concepts & Practices of Information Resources Management in Modern Organizations

Context-Aware Approach for Restaurant Recommender Systems

Context-Aware Approach for Restaurant Recommender Systems
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Author(s): Haoxian Feng (University of Ottawa, Canada) and Thomas Tran (University of Ottawa, Canada)
Copyright: 2018
Pages: 15
Source title: Encyclopedia of Information Science and Technology, Fourth Edition
Source Author(s)/Editor(s): Mehdi Khosrow-Pour, D.B.A. (Information Resources Management Association, USA)
DOI: 10.4018/978-1-5225-2255-3.ch153


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This paper addresses the issue of how to effectively use users' historical data in restaurant recommender systems, as opposed to systems, such as FindMe, that only rely on online operations. Towards that end, the authors propose a bias-based SVD method as the underlying recommendation algorithm and test it against the traditional item-based collaborative filtering method on the Entrée restaurant dataset. The results are promising as the obtained Root-Mean-Square-Error (RMSE) values reach 0.58 for the SVD and 0.62 for the item-based system. Researchers can extend the transformation from user behaviors to ratings in more application domains other than the restaurant one.

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