期刊名称：International Journal of Advanced Computer Science and Applications(IJACSA)
印刷版ISSN：2158-107X
电子版ISSN：2156-5570
出版年度：2020
卷号：11
期号：3
DOI：10.14569/IJACSA.2020.0110341
出版社：Science and Information Society (SAI)
摘要：The use of data mining techniques in the field of auctions has attracted considerable interest from the research community. In auctions, the users try to achieve the highest gain and avoid loss as much as possible. Therefore, data mining techniques can be implemented in the auctioning domain to develop an intelligent method that can be used by the users in online auctions. However, determining the factors that affect the result of an auction, especially the initial price, is critical. In addition, the intelligent system must be established based on clean data to ensure the accuracy of the results. In this paper, we propose an intelligent system (classifier) to predict the initial price of auctions. The proposed system uses the double smoothing method (DSM) for data cleaning in terms of preprocessing. This system is implemented on a data set collected from the eBay website and cleaned using the proposed DSM. In the training phase, the CART technique is employed for the classifier construction. Compared to similar techniques, the proposed system exhibits a better performance in terms of the accuracy and robustness against noisy data, as determined using ROC curves.
