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| Automated Negotiation Decision Model Based on Classifier Fusion |
| PENG Yan-Bin-1, ZHENG Zhi-Jun-1, YU Cheng-Bo-2, LI Ji-Ming-3 |
| (1. School of Information and Electronic Engineering, Zhejiang University of Science and Technology, Hangzhou 310023, China; 2. School of Computer Science and Technology, Zhejiang University, Hangzhou 310027, China; 3. Department of Forensic Science, Zhejiang Police College, Hangzhou 310053, China) |
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Abstract Due to the confidentiality of information in e-commerce environment, negotiation participants can not get opponent’s negotiation preferences, thereby affecting the negotiation performance. To solve this, an automated negotiation decision model based on classifier fusion was proposed. The model incorporates support vector machine and Bayesian classifier by combining the advantages of both, improving the effect of classification learning of negotiation preferences. Based on accurate estimation of opponent’s negotiation preference, a particle swarm optimization algorithm was used to search the optimal counter proposal. The experimental data show that the new method is better than the single classifier, and can maintain a high total negotiation utility in the noisy small scale training set.
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Received: 02 May 2012
Published: 28 April 2013
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