PODS '95 Proceedings of the fourteenth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems
Data mining: concepts and techniques
Data mining: concepts and techniques
Efficient Search Techniques for Multi-Attribute Bilateral Negotiation Strategies
ISEC '02 Proceedings of the Third International Symposium on Electronic Commerce
An agenda-based framework for multi-issue negotiation
Artificial Intelligence
Learning on opponent's preferences to make effective multi-issue negotiation trade-offs
ICEC '04 Proceedings of the 6th international conference on Electronic commerce
Applications of Data Mining in E-Business Finance: Introduction
Proceedings of the 2008 conference on Applications of Data Mining in E-Business and Finance
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Negotiation is a process between self-interested agents trying to reach an agreement on one or multiple issues in an ecommerce domain. The knowledge of an agent about the opponents' strategies improves the negotiation outcome. However, an agent negotiates with incomplete information about its opponent. Given this, to detect the opponent's strategy, we can use the similarity between opponents' strategies. In this paper we present a method for measuring the similarity between negotiators' strategies. Offers are generated by the agent's strategy therefore our similarity measure is based on the history of offers in negotiation sessions. We extended the Levenshtein distance technique to detect similarity between strategies. We implement this measure and experimentally show that the result of using the measure improves the recognition of the opponent's strategy.