Local experts finding using user comments in location-based social networks

被引：7
|
作者：
Cao, Jiuxin [1 ]
Yang, Yuntao [2 ]
Cao, Biwei [3 ]
Xue, Lingyun [2 ]
Li, Shancang [4 ]
Iqbal, Muddesar [5 ]
Mumtaz, Shahid [6 ]
机构：
[1] Southeast Univ, Sch Cyber Sci & Engn, Key Lab Comp Network Technol Jiangsu Prov, Nanjing, Jiangsu, Peoples R China
[2] Southeast Univ, Sch Comp Sci & Engn, Nanjing, Jiangsu, Peoples R China
[3] Australia Natl Univ, Coll Engn & Comp Sci, Canberra, ACT, Australia
[4] Univ West England, Dept Comp Sci & Creat Technol, Bristol, Avon, England
[5] London South Bank Univ, Sch Comp, London, England
[6] Univ Santiago, Inst Telecomunicacoes, Aveiro, Portugal
来源：
TRANSACTIONS ON EMERGING TELECOMMUNICATIONS TECHNOLOGIES | 2019年 / 30卷 / 09期
基金：
中国国家自然科学基金;
关键词：
ARCHITECTURE;
D O I：
10.1002/ett.3600
中图分类号：
TN [电子技术、通信技术];
学科分类号：
0809 ;
摘要：
The opinions of local experts in the location-based social network are of great significance to the collection and dissemination of local information. In this paper, we investigated in-depth how the user comments can be used to identify the local expert over social networks. We first illustrate the existences of potential local experts in a social network using a scored model by considering the personal profiles, comments, friend relationship, and location preferences. Then, a multidimensional model is proposed to evaluate the local expert candidates and a local expert discovery algorithm is proposed to identify local experts. Meanwhile, a scoring algorithm is proposed to train the weights in the model. Finally, an expert recommendation list can be given based on the score ranks of the candidates. Experimental results demonstrate the effectiveness of proposed model and algorithms.
引用
收藏
页数：18
相关论文
共 50 条
  • [21] Personality and location-based social networks
    Chorley, Martin J.
    Whitaker, Roger M.
    Allen, Stuart M.
    [J]. COMPUTERS IN HUMAN BEHAVIOR, 2015, 46 : 45 - 56
  • [22] Constructing a Desiring User: Discourse, Rurality, and Design in Location-Based Social Networks
    Hardy, Jean
    Lindtner, Silvia
    [J]. CSCW'17: PROCEEDINGS OF THE 2017 ACM CONFERENCE ON COMPUTER SUPPORTED COOPERATIVE WORK AND SOCIAL COMPUTING, 2017, : 13 - 25
  • [23] Context-aware user preferences prediction on location-based social networks
    Wang, Fan
    Meng, Xiangwu
    Zhang, Yujie
    [J]. JOURNAL OF INTELLIGENT INFORMATION SYSTEMS, 2019, 53 (01) : 51 - 67
  • [24] Context-aware user preferences prediction on location-based social networks
    Fan Wang
    Xiangwu Meng
    Yujie Zhang
    [J]. Journal of Intelligent Information Systems, 2019, 53 : 51 - 67
  • [25] Urban Area Function Zoning Based on User Relationships in Location-Based Social Networks
    Hao, Fei
    Zhang, Junzhe
    Duan, Zongtao
    Zhao, Liang
    Guo, Lantian
    Park, Doo-Soon
    [J]. IEEE ACCESS, 2020, 8 (08): : 23487 - 23495
  • [26] Contextual location recommendation for location-based social networks by learning user intentions and contextual triggers
    Seyyed Mohammadreza Rahimi
    Behrouz Far
    Xin Wang
    [J]. GeoInformatica, 2022, 26 : 1 - 28
  • [27] Contextual location recommendation for location-based social networks by learning user intentions and contextual triggers
    Rahimi, Seyyed Mohammadreza
    Far, Behrouz
    Wang, Xin
    [J]. GEOINFORMATICA, 2022, 26 (01) : 1 - 28
  • [28] A POI group recommendation method in location-based social networks based on user influence
    Sojahrood, Zahra Bahari
    Taleai, Mohammad
    [J]. EXPERT SYSTEMS WITH APPLICATIONS, 2021, 171
  • [29] Local Experts Finding Across Multiple Social Networks
    Ma, Yuliang
    Yuan, Ye
    Wang, Guoren
    Wang, Yishu
    Ma, Delong
    Cui, Pengjie
    [J]. DATABASE SYSTEMS FOR ADVANCED APPLICATIONS (DASFAA 2019), PT II, 2019, 11447 : 536 - 554
  • [30] Local-entity resolution for building location-based social networks by using stay points
    Minatel, Diego
    Ferreira, Vinicius
    Lopes, Alneu de Andrade
    [J]. THEORETICAL COMPUTER SCIENCE, 2021, 851 : 62 - 76
12345