NDLI: A Heuristic Approach for Context-Aware Recommendation Using Rough Set Theory

Content Provider	IET Digital Library
Author	E, Ming H G, Tao D O N U, Yi L I
Abstract	Context-aware recommender systems, aiming to further improve performance accuracy and user satisfaction by fully utilizing contextual information, have recently become one of the hottest topics in the domain of recommender systems. However, not all contextual information might be relevant or useful for recommendation purposes, and little work has been done on measuring how important the contextual information for recommendation. We propose a heuristic optimization algorithm based on rough set theory and collaborative filtering to using contextual information more efficiently for boosting recommendation. Our approach involves three processes. First, significant attributes to represent contextual information are extracted and measured to identify recommended items using rough set theory. Second, the user similarity is evaluated in a target context consideration. Third, collaborative filtering is applied to recommend appropriate items. We perform an empirical comparison of three approaches on two real-world data sets. The experimental results show that the proposed approach generates more accurate predictions.
Starting Page	500
Ending Page	506
Page Count	7
ISSN	10224653
Volume Number	27
e-ISSN	20755597
Issue Number	Issue 3, May (2018)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/cje/27/3
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/cje.2018.03.016
Journal	Chinese Journal of Electronics
Publisher Date	2018-05-01
Access Restriction	Open
Rights Holder	© Chinese Institute of Electronics
Subject Keyword	Collaborative Filtering Combinatorial Mathematics Context-aware Recommendation Context-aware Recommender System Contextual Information Heuristic Approach Heuristic Optimization Algorithm Information Network Information Retrieval Technique Optimisation Optimisation Technique Pervasive Computing Recommender System Rough Set Theory Ubiquitous Ubiquitous Computing User Satisfaction
Content Type	Text
Resource Type	Article
Subject	Applied Mathematics Electrical and Electronic Engineering

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