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A Matching Approach to Factor Scores Based on Online Sponsored Search Auction
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Author(s): Xiaohui Li (Computer Science and Technology College, Harbin Engineering University, Harbin, China), Hongbin Dong (Computer Science and Technology College, Harbin Engineering University, Harbin, China), Yang Zhou (College of Humanities and Social Sciences, Harbin Engineering University, Harbin, China)and Jun He (Department of Computer Science Aberystwyth University, Aberystwyth, UK)
Copyright: 2018
Volume: 6
Issue: 1
Pages: 20
Source title:
International Journal of Software Innovation (IJSI)
Editor(s)-in-Chief: Roger Y. Lee (Central Michigan University, USA)and Lawrence Chung (The University of Texas at Dallas, USA)
DOI: 10.4018/IJSI.2018010102
PurchaseView on the publisher's website for pricing and purchasing information.
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Abstract
How does a search engine company decide which advertisements to display for each query to maximize its revenue? This turns out to be a generalization of the online bipartite matching problem. In this paper, search engines decide the strategy to allocate resources with an advertiser credibility factor under budget constraints. Based on the optimal algorithm, which is the notion of a trade-off revealing LP, this paper remains the competitive ratio as 1-1/e with an advertiser credibility factor. During the ranking in the keywords auctions, the authors calculate factor scores. The new arrival keywords should match to the advertisement which has the maximum factor scores. The amount of spent money, budget constraints, CTR (Click Through Rate) and a credibility factor are added to the trade-off function using in the authors' algorithms. In the long term, users tend to use the search engine with high credibility, which will bring greater revenues. The search engine will attract advertisers to bid on keywords and improve their credibility actively.
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