Abstract
As the online auctioning sites grew, it became necessary to restrict or forbid auctions for various items. For this purpose, online auctioning companies assign special personnel, a large team of monitoring experts, to monitor the items posted on the web to ensure a safe and healthy online trading atmosphere. This process costs a lot for such companies and also takes a lot of time. In this research we propose a solution to this problem as an automated intelligent monitoring system which uses machine learning and data mining algorithms, in particular document classification, to monitor new items. Our results show that this approach is reliable and it reduces the monitoring cost and time.
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Seifi, F., Rastgoo, M. (2011). Intelligent Monitoring System for Online Listing and Auctioning. In: Babin, G., Stanoevska-Slabeva, K., Kropf, P. (eds) E-Technologies: Transformation in a Connected World. MCETECH 2011. Lecture Notes in Business Information Processing, vol 78. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-20862-1_17
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DOI: https://doi.org/10.1007/978-3-642-20862-1_17
Publisher Name: Springer, Berlin, Heidelberg
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