Machine Learning for Consumers and Markets

被引:0
|
作者
Wang, Wen [1 ]
Zhao, Han [2 ]
Lee, Dokyun D. K. [1 ]
Chen, George H. [1 ]
机构
[1] Carnegie Mellon Univ, Pittsburgh, PA 15213 USA
[2] Univ Illinois, Champaign, IL USA
关键词
Machine learning; business intelligence; consumers and markets;
D O I
10.1145/3447548.3469478
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Consumers leave digital footprints through large volumes of heterogeneous data which is a wealth of commercial value for firms, waiting to be mined. While there are initial success stories, this area is still under-explored. Further research and communication between the ML community and business community are needed to better align the objectives and create more successful applications. While machine learning is equipped to handle a variety of raw data for predictive tasks, without the theoretical insights from economics and consumer behavior to guide ML models, extracting generalizable insights with clear managerial implications and formulating impactful policies remain elusive. This workshop aims to promote further communication between these disciplines to foster synergistic development of impactful research that could benefit one another.
引用
收藏
页码:4165 / 4166
页数:2
相关论文
共 50 条
  • [1] Machine Learning for End Consumers
    Fong, Alvis
    Usman, Muhammad
    [J]. IEEE CONSUMER ELECTRONICS MAGAZINE, 2020, 9 (05) : 77 - 78
  • [2] Machine Learning In Power Markets
    Farooqi, Bilal Asghar
    Kazmi, Ali Abbas
    Janjua, Abdul Kashif
    [J]. 2019 2ND INTERNATIONAL CONFERENCE ON COMPUTING, MATHEMATICS AND ENGINEERING TECHNOLOGIES (ICOMET), 2019,
  • [3] Machine Learning in Futures Markets
    Waldow, Fabian
    Schnaubelt, Matthias
    Krauss, Christopher
    Fischer, Thomas Gunter
    [J]. JOURNAL OF RISK AND FINANCIAL MANAGEMENT, 2021, 14 (03)
  • [4] On AI, Markets and Machine Learning
    Parkes, David C.
    [J]. AAMAS'17: PROCEEDINGS OF THE 16TH INTERNATIONAL CONFERENCE ON AUTONOMOUS AGENTS AND MULTIAGENT SYSTEMS, 2017, : 2 - 2
  • [5] A Learning Approach for Strategic Consumers in Smart Electricity Markets
    Foti, Magda
    Vavalis, Manolis
    [J]. 2015 6TH INTERNATIONAL CONFERENCE ON INFORMATION, INTELLIGENCE, SYSTEMS AND APPLICATIONS (IISA), 2015,
  • [6] Machine Learning Applied to Energy Efficiency of Large Consumers
    Pereira, L. S. B.
    Rodrigues, R. N.
    Massuyama, G. A.
    Aranha Neto, E. A. C.
    [J]. 2019 IEEE CHILEAN CONFERENCE ON ELECTRICAL, ELECTRONICS ENGINEERING, INFORMATION AND COMMUNICATION TECHNOLOGIES (CHILECON), 2019,
  • [7] Medicalization, markets and consumers
    Conrad, Peter
    Leiter, Valerie
    [J]. JOURNAL OF HEALTH AND SOCIAL BEHAVIOR, 2004, 45 : 158 - 176
  • [8] AI, Machine Learning and sentiment analysis applied to financial markets and consumer markets
    Messina, Enza
    Erlwein-Sayer, Christina
    Mitra, Gautam
    [J]. COMPUTATIONAL MANAGEMENT SCIENCE, 2020, 17 (04) : 493 - 494
  • [9] AI, Machine Learning and sentiment analysis applied to financial markets and consumer markets
    Enza Messina
    Christina Erlwein-Sayer
    Gautam Mitra
    [J]. Computational Management Science, 2020, 17 : 493 - 494
  • [10] Dreaming machine learning: Lipschitz extensions for reinforcement learning on financial markets
    Calabuig, J. M.
    Falciani, H.
    Sanchez-Perez, E. A.
    [J]. NEUROCOMPUTING, 2020, 398 : 172 - 184