Attention-Aware Collaboration Modeling

被引:0
|
作者
Fan, Shaokun [1 ]
Zhao, J. Leon [1 ]
机构
[1] City Univ Hong Hong, Dept Informat Syst, Kowloon Tong, Hong Kong, Peoples R China
关键词
Attention-aware; Collaboration modeling; Attention stress;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Recently, a great variety of web-based collaboration support technologies (CSTs) have become available for people to collaborate for various purposes. On the other hand, CSTs are leading to more attention stress - more and more people are becoming overwhelmed by many simultaneous projects and the associated tasks. However, little research has been done on how to design collaboration management mechanisms that can help managers control collaboration activities for better collective efficiency. We lay the foundation of research in this regard by developing a model of team collaboration while emphasizing the attention aspects of collaboration, which we refer to as Attention-Aware Collaboration Modeling (AACM). In this paper, we present core concepts and basic principles of attention-aware collaboration management based on Attention Economy Theory.
引用
收藏
页码:347 / 355
页数:9
相关论文
共 50 条
  • [1] Lightweight Contrast Modeling for Attention-Aware Visual Localization
    Huang, Lili
    Li, Guanbin
    Li, Ya
    Lin, Liang
    2019 INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA), 2019, : 2104 - 2110
  • [2] Attention-Aware Answers of the Crowd
    Tu, Jingzheng
    Yu, Guoxian
    Wang, Jun
    Domeniconi, Carlotta
    Zhang, Xiangliang
    PROCEEDINGS OF THE 2020 SIAM INTERNATIONAL CONFERENCE ON DATA MINING (SDM), 2020, : 451 - 459
  • [3] Attention-Aware Invertible Hashing Network
    Li, Shanshan
    Cai, Qiang
    Li, Zhuangzi
    Li, Haisheng
    Zhang, Naiguang
    Cao, Jian
    IMAGE AND GRAPHICS, ICIG 2019, PT III, 2019, 11903 : 409 - 420
  • [4] Towards Attention-aware Foveated Rendering
    Krajancich, Brooke
    Kellnhofer, Petr
    Wetzstein, Gordon
    ACM TRANSACTIONS ON GRAPHICS, 2023, 42 (04):
  • [5] Attention-Aware Heterogeneous Graph Neural Network
    Jintao Zhang
    Quan Xu
    Big Data Mining and Analytics, 2021, 4 (04) : 233 - 241
  • [6] Attention-Aware Multi-View Stereo
    Luo, Keyang
    Guan, Tao
    Ju, Lili
    Wang, Yuesong
    Chen, Zhuo
    Luo, Yawei
    2020 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR), 2020, : 1587 - 1596
  • [7] AwToolkit: Attention-Aware User Interface Widgets
    Garrido, Juan E.
    Penichet, Victor M. R.
    Lozano, Maria D.
    Quigley, Aaron
    Kristensson, Per Ola
    PROCEEDINGS OF THE 2014 INTERNATIONAL WORKING CONFERENCE ON ADVANCED VISUAL INTERFACES, AVI 2014, 2014, : 9 - 16
  • [8] Attention-Aware Heterogeneous Graph Neural Network
    Zhang, Jintao
    Xu, Quan
    BIG DATA MINING AND ANALYTICS, 2021, 4 (04) : 233 - 241
  • [9] Attention-Aware Disparity Control in interactive environments
    Celikcan, Ufuk
    Cimen, Gokcen
    Kevinc, E. Bengu
    Capin, Tolga
    VISUAL COMPUTER, 2013, 29 (6-8): : 685 - 694
  • [10] MARS: Memory Attention-Aware Recommender System
    Zheng, Lei
    Lu, Chun-Ta
    He, Lifang
    Xie, Sihong
    He, Huang
    Li, Chaozhuo
    Noroozi, Vahid
    Dong, Bowen
    Yu, Philip S.
    2019 IEEE INTERNATIONAL CONFERENCE ON DATA SCIENCE AND ADVANCED ANALYTICS (DSAA 2019), 2019, : 11 - 20