Building and evaluating a location-based service recommendation system with a preference adjustment mechanism

被引:68
|
作者
Kuo, Mu-Hsing [1 ]
Chen, Liang-Chu [2 ]
Liang, Chien-Wen
机构
[1] Univ Victoria, Univ Hlth Informat Sci, STN CSC, Victoria, BC V8W 3P5, Canada
[2] Natl Def Univ, Dept Informat Management, Taipei, Taiwan
关键词
Location-based service (LBS); Recommendation system; Preference adjustment;
D O I
10.1016/j.eswa.2008.02.014
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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 oil 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%. (C) 2008 Elsevier Ltd. All rights reserved.
引用
收藏
页码:3543 / 3554
页数:12
相关论文
共 50 条
  • [1] Towards Building and Evaluating a Personalized Location-Based Recommender System
    Duan, Rubing
    Goh, Rick Siow Mong
    Yang, Feng
    Tan, Yong Kiam
    Valenzuela, Jesus F. B.
    [J]. 2014 IEEE INTERNATIONAL CONFERENCE ON BIG DATA (BIG DATA), 2014, : 43 - 48
  • [2] Location-Based Service Using Ontology and Collaborative Recommendation
    Hu, Lantao
    Tong, Qiuli
    Du, Zhao
    Liu, Yongqi
    Tang, Yeming
    [J]. 2014 INTERNATIONAL CONFERENCE ON INFORMATION SCIENCE, ELECTRONICS AND ELECTRICAL ENGINEERING (ISEEE), VOLS 1-3, 2014, : 652 - +
  • [3] Location-based service with context data for a restaurant recommendation
    Lee, Bae-Hee
    Kim, Heung-Nam
    Jung, Jin-Guk
    Jo, Geun-Sik
    [J]. DATABASE AND EXPERT SYSTEMS APPLICATIONS, PROCEEDINGS, 2006, 4080 : 430 - 438
  • [4] Location-based collaborative filtering for web service recommendation
    Venkatachalaappaswamy, Mareeswari
    Ramaraj, Vijayan
    Ravichandran, Saranya
    [J]. Recent Patents on Computer Science, 2019, 12 (01) : 34 - 40
  • [5] Time and Location-Based Hybrid Recommendation System
    Tong, Junyu
    Ma, Hongyuan
    Liu, Wei
    Wang, Bo
    [J]. 2017 IEEE 2ND INTERNATIONAL CONFERENCE ON BIG DATA ANALYSIS (ICBDA), 2017, : 677 - 683
  • [6] Research on Location-based Personalized Recommendation System
    Gao, Huan
    Tian, Xi
    Fu, Xiangling
    [J]. MECHANICAL DESIGN AND POWER ENGINEERING, PTS 1 AND 2, 2014, 490-491 : 1493 - 1496
  • [7] Friend Recommendation Considering Preference Coverage in Location-Based Social Networks
    Yu, Fei
    Che, Nan
    Li, Zhijun
    Li, Kai
    Jiang, Shouxu
    [J]. ADVANCES IN KNOWLEDGE DISCOVERY AND DATA MINING, PAKDD 2017, PT II, 2017, 10235 : 91 - 105
  • [8] Location-based Hierarchical Matrix Factorization for Web Service Recommendation
    He, Pinjia
    Zhu, Jieming
    Zheng, Zibin
    Xu, Jianlong
    Lyu, Michael R.
    [J]. 2014 IEEE 21ST INTERNATIONAL CONFERENCE ON WEB SERVICES (ICWS 2014), 2014, : 297 - 304
  • [9] Location-based recommendation system using Bayesian user's preference model in mobile devices
    Park, Moon-Hee
    Hong, Jin-Hyuk
    Cho, Sung-Bae
    [J]. UBIQUITOUS INTELLIGENCE AND COMPUTING, PROCEEDINGS, 2007, 4611 : 1130 - +
  • [10] Location-based deep factorization machine model for service recommendation
    Wang, Qingren
    Zhang, Min
    Zhang, Yiwen
    Zhong, Jinqin
    Sheng, Victor S.
    [J]. APPLIED INTELLIGENCE, 2022, 52 (09) : 9899 - 9918