A Service Mode of Expert Finding in Social Network

被引:3
|
作者
Li, Xiu [1 ]
Ma, Jianguo [1 ]
Yang, Yujiu [1 ]
Wang, Dongzhi [1 ]
机构
[1] Tsinghua Univ, Grad Sch Shenzhen, Shenzhen Key Lab Informat Sci & Technol, Shenzhen 518057, Peoples R China
来源
2013 INTERNATIONAL CONFERENCE ON SERVICE SCIENCES (ICSS 2013) | 2013年
关键词
service mode; Explicit Semantic Analysis; ESA; social network; sina microblog; expert finding; language model; social relationship; expertise propagation; framework;
D O I
10.1109/ICSS.2013.48
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Expert finding addresses the task of finding the right person with the appropriate knowledge or skills. State-of-the-art expert finding algorithms usually estimate the relevance between the query and the support documents of candidates using language model. However, the language model has a limitation that all the query terms should occur in each support document, which results in some real experts cannot be searched. So for the process of analyzing textual content, we consider using a new model based on Explicit Semantic Analysis (ESA) rather than the language model. With the development of Internet technology, this is not the only way to find experts. In the modern social media, we can record person's social relationships which might be available for expert finding task. A simple truth is: a person's connections with experts will provide the potential evidence that he is a real expert. In this paper, we propose a new service pattern for expert finding that accounts for both documents' content and social relationships. The relationships in the social network are used in re-ranking experts on a given topic.
引用
收藏
页码:220 / 223
页数:4
相关论文
共 50 条
  • [1] A Topic-Specific Contextual Expert Finding Method in Social Network
    Xie, Xiaoqin
    Li, Yijia
    Zhang, Zhiqiang
    Pan, Haiwei
    Han, Shuai
    WEB TECHNOLOGIES AND APPLICATIONS, PT I, 2016, 9931 : 292 - 303
  • [2] A Model for Expert Finding based on Social Network Structure and Underlying Information Diffusion Network
    Kardan, Ahmad
    Mohtaj, Salar
    2013 5TH CONFERENCE ON INFORMATION AND KNOWLEDGE TECHNOLOGY (IKT), 2013, : 472 - 477
  • [3] Expert Finding with Explicit Semantic Analysis
    Ma, Jianguo
    Yang, Yujiu
    Wang, Liangwei
    FUZZY SYSTEMS, KNOWLEDGE DISCOVERY AND NATURAL COMPUTATION SYMPOSIUM (FSKDNC 2013), 2013, : 468 - 479
  • [4] Expert Finding Considering Dynamic Profiles and Trust in Social Networks
    Bok, Kyoungsoo
    Jeon, Inbae
    Lim, Jongtae
    Yoo, Jaesoo
    ELECTRONICS, 2019, 8 (10)
  • [5] Misinformation-oriented expert finding in social networks
    Guohui Li
    Ming Dong
    Fuming Yang
    Jun Zeng
    Jiansen Yuan
    Congyuan Jin
    Nguyen Quoc Viet Hung
    Phan Thanh Cong
    Bolong Zheng
    World Wide Web, 2020, 23 : 693 - 714
  • [6] Towards comprehensive expert finding with a hierarchical matching network
    Peng, Qiyao
    Wang, Wenjun
    Liu, Hongtao
    Wang, Yinghui
    Xu, Hongyan
    Shao, Minglai
    KNOWLEDGE-BASED SYSTEMS, 2022, 257
  • [7] Misinformation-oriented expert finding in social networks
    Li, Guohui
    Dong, Ming
    Yang, Fuming
    Zeng, Jun
    Yuan, Jiansen
    Jin, Congyuan
    Nguyen Quoc Viet Hung
    Phan Thanh Cong
    Zheng, Bolong
    WORLD WIDE WEB-INTERNET AND WEB INFORMATION SYSTEMS, 2020, 23 (02): : 693 - 714
  • [8] EFCNN: A Restricted Convolutional Neural Network for Expert Finding
    Zhao, Yifeng
    Tang, Jie
    Du, Zhengxiao
    ADVANCES IN KNOWLEDGE DISCOVERY AND DATA MINING, PAKDD 2019, PT II, 2019, 11440 : 96 - 107
  • [9] Context based user ranking in forums for expert finding using WordNet dictionary and social network analysis
    Amin Omidvar
    Mehdi Garakani
    Hamid R. Safarpour
    Information Technology and Management, 2014, 15 : 51 - 63
  • [10] Context based user ranking in forums for expert finding using WordNet dictionary and social network analysis
    Omidvar, Amin
    Garakani, Mehdi
    Safarpour, Hamid R.
    INFORMATION TECHNOLOGY & MANAGEMENT, 2014, 15 (01) : 51 - 63