A Method for Constructing Engineering-Biology Domain Knowledge Network Oriented Toward Collective Intelligence Innovation Design

Haibo Liu, Lin Gong*, Xianpeng Zhang, Xuqiang Chang, Hanhun Li, Weipeng Jiang

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In the context of the era of information, the growth of personalized user needs and the development of Internet plus technology have brought new challenges and opportunities to product innovation design. As an emerging design mode, collective intelligence design can acquire design knowledge through group wisdom and extensive range to improve the market adaptability of products and the innovation ability of enterprises. As a kind of long-distance knowledge, biology domain knowledge can effectively play the incentive role of cross-domain knowledge in the collective intelligence design process. However, there is currently no effective way of combining engineering with biology domain knowledge to underpin the design process. To address this issue, we propose a method for constructing an engineering-biology domain knowledge network for collective intelligence innovation design: A cross-domain knowledge representation model is constructed to achieve unified representation of engineering and biology domain knowledge; By using cross-domain entity extraction and relationship generation methods, an engineering-biology domain knowledge network is automatically constructed. This method provides a new perspective for cross-domain knowledge motivation and inspiration in collective intelligence innovation design. Through the representation and relationship generation of cross-domain knowledge, our engineering-biology domain knowledge network can provide designers with long-distance design knowledge incentives, improving the quality and innovation of generated solutions.

Original languageEnglish
Title of host publication2024 International Conference on Automation in Manufacturing, Transportation and Logistics, ICaMaL 2024
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798350378658
DOIs
Publication statusPublished - 2024
Event2024 International Conference on Automation in Manufacturing, Transportation and Logistics, ICaMaL 2024 - Hong Kong, Hong Kong
Duration: 7 Aug 20249 Aug 2024

Publication series

Name2024 International Conference on Automation in Manufacturing, Transportation and Logistics, ICaMaL 2024

Conference

Conference2024 International Conference on Automation in Manufacturing, Transportation and Logistics, ICaMaL 2024
Country/TerritoryHong Kong
CityHong Kong
Period7/08/249/08/24

Keywords

  • collective intelligence innovation design
  • cross-domain knowledge network
  • knowledge inspiration

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