Machine learning for negotiation knowledge discovery in e-Marketplaces

Raymond Y. K. Lau

doi:10.1109/ICEBE.2007.38

Machine learning for negotiation knowledge discovery in e-Marketplaces

Raymond Y. K. Lau

Department of Information Systems

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

1 Citation (Scopus)

Abstract

The level of autonomy and the efficiency of e-Marketplaces can be improved if automated negotiation support is available. Some parametric learning negotiation models have been proposed recently. These models allow a negotiator to learn the opponents' preferences based on previous offer exchanges. Nevertheless, these models make strong assumptions about the particular negotiation mechanism employed by the respective negotiation agent. This paper illustrates the design, development, and evaluation of a non-parametric negotiation knowledge discovery method which is underpinned by the well-known Bayesian learning paradigm. This method can discovery vital information about a negotiator's preferences without making any assumption about the underlying negotiation mechanism employed by the negotiator. According to our empirical testing, the proposed negotiation knowledge discovery method can speed up the negotiation prvcess while maintaining the negotiation effectiveness. Our research work opens the door to the development of intelligent negotiation mechanisms to enhance modern e-Marketplaces. © 2007 IEEE.

Original language	English
Title of host publication	Proceedings - ICEBE 2007: IEEE International Conference on e-Business Engineering - Workshops: SOAIC 2007; SOSE 2007; SOKM 2007
Pages	239-246
DOIs	https://doi.org/10.1109/ICEBE.2007.38
Publication status	Published - 2007
Event	IEEE International Conference on e-Business Engineering (ICEBE 2007) ; IEEE International Workshop on Service-Oriented Applications, Integration and Collaboration (SOAIC 2007) ; IEEE International Workshop on Service-Oriented System Engineering (SOSE 2007) ; IEEE International Workshop on Service-Oriented Knowledge Management (SOKM 2007) - , Hong Kong, China Duration: 24 Oct 2007 → 26 Oct 2007 https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=4402050

Conference

Conference	IEEE International Conference on e-Business Engineering (ICEBE 2007) ; IEEE International Workshop on Service-Oriented Applications, Integration and Collaboration (SOAIC 2007) ; IEEE International Workshop on Service-Oriented System Engineering (SOSE 2007) ; IEEE International Workshop on Service-Oriented Knowledge Management (SOKM 2007)
Place	Hong Kong, China
Period	24/10/07 → 26/10/07
Internet address	https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=4402050

Research Keywords

Automated negotiations
Bayesian learning
e-Marketplaces
Knowledge discovery
Machine learning

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title = "Machine learning for negotiation knowledge discovery in e-Marketplaces",

abstract = "The level of autonomy and the efficiency of e-Marketplaces can be improved if automated negotiation support is available. Some parametric learning negotiation models have been proposed recently. These models allow a negotiator to learn the opponents' preferences based on previous offer exchanges. Nevertheless, these models make strong assumptions about the particular negotiation mechanism employed by the respective negotiation agent. This paper illustrates the design, development, and evaluation of a non-parametric negotiation knowledge discovery method which is underpinned by the well-known Bayesian learning paradigm. This method can discovery vital information about a negotiator's preferences without making any assumption about the underlying negotiation mechanism employed by the negotiator. According to our empirical testing, the proposed negotiation knowledge discovery method can speed up the negotiation prvcess while maintaining the negotiation effectiveness. Our research work opens the door to the development of intelligent negotiation mechanisms to enhance modern e-Marketplaces. {\textcopyright} 2007 IEEE.",

keywords = "Automated negotiations, Bayesian learning, e-Marketplaces, Knowledge discovery, Machine learning",

author = "Lau, \{Raymond Y. K.\}",

year = "2007",

doi = "10.1109/ICEBE.2007.38",

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pages = "239--246",

booktitle = "Proceedings - ICEBE 2007: IEEE International Conference on e-Business Engineering - Workshops: SOAIC 2007; SOSE 2007; SOKM 2007",

note = "IEEE International Conference on e-Business Engineering (ICEBE 2007) ; IEEE International Workshop on Service-Oriented Applications, Integration and Collaboration (SOAIC 2007) ; IEEE International Workshop on Service-Oriented System Engineering (SOSE 2007) ; IEEE International Workshop on Service-Oriented Knowledge Management (SOKM 2007) ; Conference date: 24-10-2007 Through 26-10-2007",

url = "https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=\&arnumber=4402050",

}

Lau, RYK 2007, Machine learning for negotiation knowledge discovery in e-Marketplaces. in Proceedings - ICEBE 2007: IEEE International Conference on e-Business Engineering - Workshops: SOAIC 2007; SOSE 2007; SOKM 2007., 4402097, pp. 239-246, IEEE International Conference on e-Business Engineering (ICEBE 2007) ; IEEE International Workshop on Service-Oriented Applications, Integration and Collaboration (SOAIC 2007) ; IEEE International Workshop on Service-Oriented System Engineering (SOSE 2007) ; IEEE International Workshop on Service-Oriented Knowledge Management (SOKM 2007), Hong Kong, China, 24/10/07. https://doi.org/10.1109/ICEBE.2007.38

Machine learning for negotiation knowledge discovery in e-Marketplaces. / Lau, Raymond Y. K.
Proceedings - ICEBE 2007: IEEE International Conference on e-Business Engineering - Workshops: SOAIC 2007; SOSE 2007; SOKM 2007. 2007. p. 239-246 4402097.

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

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T1 - Machine learning for negotiation knowledge discovery in e-Marketplaces

AU - Lau, Raymond Y. K.

PY - 2007

Y1 - 2007

N2 - The level of autonomy and the efficiency of e-Marketplaces can be improved if automated negotiation support is available. Some parametric learning negotiation models have been proposed recently. These models allow a negotiator to learn the opponents' preferences based on previous offer exchanges. Nevertheless, these models make strong assumptions about the particular negotiation mechanism employed by the respective negotiation agent. This paper illustrates the design, development, and evaluation of a non-parametric negotiation knowledge discovery method which is underpinned by the well-known Bayesian learning paradigm. This method can discovery vital information about a negotiator's preferences without making any assumption about the underlying negotiation mechanism employed by the negotiator. According to our empirical testing, the proposed negotiation knowledge discovery method can speed up the negotiation prvcess while maintaining the negotiation effectiveness. Our research work opens the door to the development of intelligent negotiation mechanisms to enhance modern e-Marketplaces. © 2007 IEEE.

AB - The level of autonomy and the efficiency of e-Marketplaces can be improved if automated negotiation support is available. Some parametric learning negotiation models have been proposed recently. These models allow a negotiator to learn the opponents' preferences based on previous offer exchanges. Nevertheless, these models make strong assumptions about the particular negotiation mechanism employed by the respective negotiation agent. This paper illustrates the design, development, and evaluation of a non-parametric negotiation knowledge discovery method which is underpinned by the well-known Bayesian learning paradigm. This method can discovery vital information about a negotiator's preferences without making any assumption about the underlying negotiation mechanism employed by the negotiator. According to our empirical testing, the proposed negotiation knowledge discovery method can speed up the negotiation prvcess while maintaining the negotiation effectiveness. Our research work opens the door to the development of intelligent negotiation mechanisms to enhance modern e-Marketplaces. © 2007 IEEE.

KW - Automated negotiations

KW - Bayesian learning

KW - e-Marketplaces

KW - Knowledge discovery

KW - Machine learning

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DO - 10.1109/ICEBE.2007.38

M3 - RGC 32 - Refereed conference paper (with host publication)

SN - 0769530036

SN - 9780769530031

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BT - Proceedings - ICEBE 2007: IEEE International Conference on e-Business Engineering - Workshops: SOAIC 2007; SOSE 2007; SOKM 2007

T2 - IEEE International Conference on e-Business Engineering (ICEBE 2007) ; IEEE International Workshop on Service-Oriented Applications, Integration and Collaboration (SOAIC 2007) ; IEEE International Workshop on Service-Oriented System Engineering (SOSE 2007) ; IEEE International Workshop on Service-Oriented Knowledge Management (SOKM 2007)

Y2 - 24 October 2007 through 26 October 2007

ER -

Machine learning for negotiation knowledge discovery in e-Marketplaces

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