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
Link To Document :
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