期刊名称：Journal of Theoretical and Applied Information Technology
印刷版ISSN：1992-8645
电子版ISSN：1817-3195
出版年度：2015
卷号：78
期号：3
出版社：Journal of Theoretical and Applied
摘要：In last two decades, Online (Web) auctions and its types took a lot of attention by researchers and business corporates. The main problem in many auction types is the fixed-closing time, which causes a phenomenon called "sniping" (i.e. submitting a bid at the final moments by one of the bidders). This paper resolved this problem by presenting a proposed type of online auctions called Least and Unique Price with Ascending Slices (LUP-AS) which is an enhanced version of LUP [6][7]. In the LUP-AS, the item price will be collected by the bidding processes. During the auction life there will be many temporary winners (who submit the least and unique price). However, the winner in this auction has to submit the least, unique but his price must be greater than the number of cancelled bids. The number of cancelled bid is a counter incremented by one when a bidder submit a least but not unique price during the auction life. The main advantages of LUP-AS are: Funny (like playing game), semi-sealed, dynamic (no fixed closing time and discard the snipers), the winner pay a very least price for item, and the seller gets the fair price. An implementation of LUP-AS uses an Artificial Neural Network in order to provide the administrators the ability to classify the bidders into groups to distribute special benefits according to each group.
