Building and evaluating a location-based service recommendation system with a preference adjustment mechanism
Expert Systems with ApplicationsPublished 3 March 2008
Mu-Hsing Kuo, Liang-Chu Chen, Chien-Wen Liang
Citations95
SJR quartileQ1
SJR score1.85
SNIP2.55
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TL;DR
In the recommendation model, an adaptive method including long-term and short-term preference adjustment to enhance the result of recommendation is conducted to present a location-based service recommendation model (LBSRM) and design a prototype system to simulate and measure the validity of LBSRM.
Abstract
The location-based service (LBS) of mobile communication and the personalization of information recommendation are two important trends in the development of electric commerce. However, many previous researches have only emphasized on one of the two trends. In this paper, we integrate the application of LBS with recommendation technologies to present a location-based service recommendation model (LBSRM) and design a prototype system to simulate and measure the validity of LBSRM. Due to the accumulation and variation of preference, in the recommendation model we conduct an adaptive method including long-term and short-term preference adjustment to enhance the result of recommendation. Research results show, with the assessments of relative index, the rate of recommendation precision could be 85.48%.
Keywords
Computer ScienceSocial Sciences
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