Abstract
Online auctions allows users to sell and buy a variety of goods, and they are now one of the most important web services. Predicting final prices on online auctions is a hard task. However, there has been much pioneering work over the past ten years. In this paper, we propose a novel method for predicting final prices using a time series splitting and clustering method to provide higher accuracy. An evaluation of the effectiveness of our method is also described in the paper. © 2012 Springer-Verlag Berlin Heidelberg.
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CITATION STYLE
Yokotani, T., Huang, H. H., & Kawagoe, K. (2012). Predicting online auction final prices using time series splitting and clustering. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7235 LNCS, pp. 207–218). https://doi.org/10.1007/978-3-642-29253-8_18
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