Information retrieval: data structures and algorithms
Information retrieval: data structures and algorithms
Information systems and economics
Communications of the ACM
Communications of the ACM
Recommender systems in e-commerce
Proceedings of the 1st ACM conference on Electronic commerce
Analysis of recommendation algorithms for e-commerce
Proceedings of the 2nd ACM conference on Electronic commerce
Insights and analyses of online auctions
Communications of the ACM
XML in a nutshell
Recommendation Systems: A Probabilistic Analysis
FOCS '98 Proceedings of the 39th Annual Symposium on Foundations of Computer Science
HICSS '01 Proceedings of the 34th Annual Hawaii International Conference on System Sciences ( HICSS-34)-Volume 7 - Volume 7
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)
Efficient bid pricing based on costing methods for internet bid systems
WISE'06 Proceedings of the 7th international conference on Web Information Systems
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
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Internet group buying systems have been widely used recently. In those systems, because the reserve price is provided by the buyer, the success rate can be decreased if the reserve price is set too low compared with the normal price. Otherwise, an unsuitable successful bid can be made if the reserve price is set too high based on inaccurate information. Likewise, the seller's providing too high a bid price can deteriorate his/her own successful bid rate, whereas a successful bid with too low a price may make no profit in the sale. Therefore, pricing agents that recommend adequate prices based on the past buying and selling history data can be helpful. In this paper, we propose two kinds of agents. One suggests reserve prices to buyers based on the past buying history database of the system. The other recommends bid prices to a seller based on the past bidding history data of the company using the cost accounting theory. Through performance experiments, we show that the successful bid rate can increase by preventing buyers from making unreasonable reserve prices. Also, we show that, for the seller, the rate of successful bids with appropriate profits can increase. Using the pricing agents, we design and implement an XML-based group buying system. Because it is based on XML standards, it has advantages such as interoperability and extendibility compared with previous proprietary electronic commerce systems.