On Generating Dominators of Customer Preferences

Jiang Bian, Weibo Wang, Xiang Zhang, Wei Weng, Arthur Huang, Zhishan Guo

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Manufacturing decisions on how to design new products have tremendous impact on the profitability of the manufacturer. This problem has recently attracted extensive research interests and motivated highly productive activities in developing the microeconomic framework for data mining and finding skyline objects in high-dimensional data. In this paper, we investigate a basic designing problem: designing products that satisfy the preferences of all customers. We formalize this problem as generating dominators (products) that dominate the preference dataset. The problem is naturally related to the microeconomic framework of data mining and the problem of finding skyline objects. The designing problem can be optimized from either the manufacturer's perspective or the customer's perspective. Our framework integrates these two perspectives and achieves optimization in a single effort. We show that this problem is NP-complete and study its computational properties. A deterministic greedy algorithm and a randomized greedy algorithm are developed. Extensive experimental evaluation on both real and simulated datasets demonstrates the effectiveness and efficiency of the proposed algorithms.

Original languageEnglish (US)
Title of host publicationProceedings - 2019 IEEE International Conference on Big Data, Big Data 2019
EditorsChaitanya Baru, Jun Huan, Latifur Khan, Xiaohua Tony Hu, Ronay Ak, Yuanyuan Tian, Roger Barga, Carlo Zaniolo, Kisung Lee, Yanfang Fanny Ye
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages10
ISBN (Electronic)9781728108582
StatePublished - Dec 2019
Event2019 IEEE International Conference on Big Data, Big Data 2019 - Los Angeles, United States
Duration: Dec 9 2019Dec 12 2019

Publication series

NameProceedings - 2019 IEEE International Conference on Big Data, Big Data 2019


Conference2019 IEEE International Conference on Big Data, Big Data 2019
Country/TerritoryUnited States
CityLos Angeles

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Networks and Communications
  • Information Systems
  • Information Systems and Management


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