Recommendation-Aware Smartphone Sensing System
ARTICLE
Mu-Yen Chen, Ming-Ni Wu, Department of Information Management, National Taichung University of Science and Technology, Taiwan ; Chia-Chen Chen, Department of Management Information Systems, National Chung Hsing University, Taiwan ; Young-Long Chen, Department of Computer Science and Information Engineering, National Taichung University of Science and Technology, Taiwan ; Hsien-En Lin, Department of Information Management, National Taichung University of Science and Technology, Taiwan
Journal of Applied Research and Technology Volume 12, Number 6, ISSN 1665-6423 Publisher: Elsevier Ltd
Abstract
The context-aware concept is to reduce the gap between users and information systems so that the information systems actively get to understand users’ context and demand and in return provide users with better experience. This study integrates the concept of context-aware with association algorithms to establish the context-aware recommendation systems (CARS). The CARS contains three modules and provides the product recommendations for users with their smartphone. First, the simple RSSI Indoor localization module (SRILM) locates the user position and detects the context information surrounding around users. Second, the Apriori recommendation module (ARM) provides effective recommended product information for users through association rules mining. The appropriate product information can be received effectiveness and greatly enhanced the recommendation service.
Citation
Chen, M.Y., Wu, M.N., Chen, C.C., Chen, Y.L. & Lin, H.E. (2014). Recommendation-Aware Smartphone Sensing System. Journal of Applied Research and Technology, 12(6), 1040-1050. Elsevier Ltd. Retrieved August 21, 2019 from https://www.learntechlib.org/p/198127/.
This record was imported from
Journal of Applied Research and Technology
on January 29, 2019.
Journal of Applied Research and Technology is a publication of Elsevier.
