To buy or not to buy: mining airfare data to minimize ticket purchase price
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Pattern Recognition and Machine Learning (Information Science and Statistics)
Pattern Recognition and Machine Learning (Information Science and Statistics)
A brief introduction to boosting
IJCAI'99 Proceedings of the 16th international joint conference on Artificial intelligence - Volume 2
Proceedings of the 20th ACM international conference on Information and knowledge management
Aggregating web offers to determine product prices
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
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Keeping in pace with the increasing importance of commerce conducted over the Web, several e-commerce websites now provide admirable facilities for helping consumers decide what product to buy and where to buy it. However, since the prices of durable and high-tech products generally fall over time, a buyer of such products is often faced with a dilemma: Should she buy the product now or wait for cheaper prices? We present the design and implementation of Prodcast, an experimental system whose goal is to help consumers decide when to buy a product. The system makes use of forecasts of future prices based on price histories of the products, incorporating features such as sales volume, seasonality, and competition in making its recommendation. We describe techniques that are well-suited for this task and present a comprehensive evaluation of their relative merits using retail sales data for electronic products. Our back-testing of the system indicates that the system is capable of helping consumers time their purchase, resulting in significant savings to them.