DocumentCode
1963660
Title
A Hybrid Case-Based Approach for Retrieving User´s Preference and Strategy in Buyer-Seller Negotiation
Author
Fang, Fang ; Xin, Ye
Author_Institution
Technol. Dept., Dalian Commodity Exchange, Dalian
fYear
2008
fDate
23-25 May 2008
Firstpage
286
Lastpage
291
Abstract
The problem of buyer-seller negotiation is extensive, which occurs not only during the negotiation period itself (the gaming problem), but also at the pre and post negotiation phases (the knowledge elicitation and commitment problems respectively). This paper focuses on the part of pre-negotiation phase and proposes a hybrid case-based approach (including CBR, ANN and PSO) in order to effectively elicit userpsilas negotiation preference and strategy for preparing the formal bargaining period. Based on the proposed CBR approach, past negotiation experiences are sufficiently recorded and effectively stored in the case database; similar previous cases are precisely retrieved and their solutions are adapted to suit the new negotiation problem. The proposed approach for retrieving negotiation knowledge in the pre-negotiation phase can share of past experience and knowledge, provide a fast but reasonable solution, and avoid unnecessary mistakes.
Keywords
case-based reasoning; game theory; neural nets; particle swarm optimisation; supply chain management; ANN; CBR; PSO; buyer-seller negotiation; gaming problem; hybrid case-based approach; supply chain management; Artificial neural networks; Databases; Evolutionary computation; Face; Humans; Information processing; Information retrieval; Supply chain management; Supply chains; Utility theory; Buyer-seller negotiation; Case-based reasoning; Information retrieved system; Supply chain management;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Processing (ISIP), 2008 International Symposiums on
Conference_Location
Moscow
Print_ISBN
978-0-7695-3151-9
Type
conf
DOI
10.1109/ISIP.2008.73
Filename
4554100
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