Machine Learning: Adaptive Negotiation Agents in E-Commerce
International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
Call for Papers | Fully Refereed | Open Access | Double Blind Peer Reviewed

ISSN: 2319-7064


Downloads: 109 | Views: 436

Review Papers | Computer Science & Engineering | India | Volume 6 Issue 3, March 2017 | Popularity: 6.2 / 10


     

Machine Learning: Adaptive Negotiation Agents in E-Commerce

Deepika Pandey, Raj Gaurang Tiwari, Pankaj Kumar


Abstract: Automated negotiation can play a vital role in the domain of e-commerce. Researches have mainly focused on negotiation protocol and strategy design in B2C section. Less work has been done in the area of B2B e-commerce which is crucially useful in dynamic negotiation to achieve better profitability for both buyer and supplier. Lack of such researches has a bottleneck in implementing automated negotiation to real business deals. This paper studies various machine learning approaches and type of agents to get better understanding of an adaptive negotiation agent. This paper tries to reveals some insights into present and future work about adaptive negotiation which may be helpful for further development of B2B e-commerce adaptive negotiation system.


Keywords: Machine learning, B2B, E-Commerce, Agents, Negotiation


Edition: Volume 6 Issue 3, March 2017


Pages: 2227 - 2233



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Deepika Pandey, Raj Gaurang Tiwari, Pankaj Kumar, "Machine Learning: Adaptive Negotiation Agents in E-Commerce", International Journal of Science and Research (IJSR), Volume 6 Issue 3, March 2017, pp. 2227-2233, https://www.ijsr.net/getabstract.php?paperid=ART20171959, DOI: https://www.doi.org/10.21275/ART20171959

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