Pricing Agents for a Group Buying System
EurAsia-ICT '02 Proceedings of the First EurAsian Conference on Information and Communication Technology
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Proceedings of the Fourteenth International Florida Artificial Intelligence Research Society Conference
An Expert Recommendation System using Concept-based Relevance Discernment
ICTAI '01 Proceedings of the 13th IEEE International Conference on Tools with Artificial Intelligence
Dynamic Service Pricing for Brokers in a Multi-Agent Economy
ICMAS '00 Proceedings of the Fourth International Conference on MultiAgent Systems (ICMAS-2000)
Dynamic Pricing for E-Commerce, an Integrated Solution
WECWIS '01 Proceedings of the Third International Workshop on Advanced Issues of E-Commerce and Web-Based Information Systems (WECWIS '01)
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COMPSAC '03 Proceedings of the 27th Annual International Conference on Computer Software and Applications
Reserve price recommendation by similarity-based time series analysis for internet auction systems
KES'06 Proceedings of the 10th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part I
A method of recommending buying points for internet shopping malls
KES'06 Proceedings of the 10th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part I
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Internet bid systems are being widely used of late. In these systems, the seller sets the bid price. When the bid price is set too high compared with the normal price, chances of a successful bid may decrease. When it is set too low, however, based on inaccurate information, it can result in a successful bid yet one with no profit at all. To resolve this problem, an agent is proposed that automatically generates bid prices for sellers based on the similarity of the bidding parameters using past bidding information as well as on various costing methods such as the high-low point method, the scatter diagram method, and the learning curve method. Performance experiments have shown that the number of successful bids with appropriate profits can be increased using the bid pricing agent. Among the costing methods, the learning curve method has shown the best performance. The manner of designing and implementing the bid pricing agent is also discussed.