An Agent-based Online Shopping System in E-commerce


  •  Ziming Zeng    

Abstract

The paper presents an agent-based shopping system. First, the system can acquire the customer’s current needs from system-customer interactions. Then the system integrates built-in expert knowledge and the customer’s current needs, and recommends optimal products based on multi-attribute decision method. In order to maintain a semantic conversation with sellers, the commodity ontology is also utilized to support sharable information format and representation. Finally, an experimental prototype based on JADE is developed. 



This work is licensed under a Creative Commons Attribution 4.0 License.
  • ISSN(Print): 1913-8989
  • ISSN(Online): 1913-8997
  • Started: 2008
  • Frequency: semiannual

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Impact Factor 2022 (by WJCI):  0.419

h-index (January 2024): 43

i10-index (January 2024): 193

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