[1] Varian H. Position auctions[J]. International Journal of Industrial Organization, 2007, 25(6):1163-1178.
[2] Edelman B, Ostrovsky M, Schwarz M. Internet advertising and the generalized second price auction: Selling billions of dollars worth of keywords[R].The American Economic Review, 2005.
[3] Group E. Online advertising: Pay per sale[J]. The Economist, 2005, 10:110-111.
[4] Michael Peterson K K, Grone F, Kirscheneder J. Performance-Based Advertising Models Extending the Principles of Profit-Driven Marketing[M].2007.
[5] Mitchell D. Click fraud and halli-bloggers[N]. New York Times, 2005, July.
[6] Penenberg A. Click fraud threatens web[N]. Wired News, 2004, October.
[7] Helft M. Google Tests an Ad Idea: Pay Only for Results[N]. New York Times, 2007, March.
[8] Yahoo. Yahoo! Search Marketing[OL].http://www.yahoosearchmarketingsea.com.
[9] Broder A, Ciccolo P, Fontoura M, et al. Search advertising using web relevance feedback[C]//Proceeding of the 17th ACM conference on Information and knowledge management.2008:1013-1022.
[10] Raghavan H, Iyer R. Probabilistic first pass retrieval for search advertising: From theory to practice[C]//Proceedings of the 19th ACM international conference on Information and knowledge management.2010:1019-1028.
[11] Krishna V. Auction theory[M].Academic press, 2009.
[12] Nazerzadeh H, Saberi A, Vohra R. Dynamic cost-per-action mechanisms and applications to online advertising[C]//Proceeding of the 17th international conference on World Wide Web.2008:179-188.
[13] Mahdian M, Tomak K. Pay-per-action model for online advertising[C]//Proceedings of the 1st international workshop on Data mining and audience intelligence for advertising.2007:1-6.
[14] Immorlica N, Jain K, Mahdian M, et al. Click fraud resistant methods for learning click-through rates[J]. Internet and Network Economics, 2005:34-45.
[15] Bagherjeiran A, Hatch A, Ratnaparkhi A. Ranking for the conversion funnel[C]//Proceeding of the 33rd international ACM SIGIR conference on Research and development in information retrieval.2010:146-153.
[16] Rey B, Kannan A. Conversion rate based bid adjustment for sponsored search[C]//Proceedings of the 19th international conference on World wide web.2010:1173-1174.
[17] Xu W, Manavoglu E, Cantu-Paz E. Temporal click model for sponsored search[C]//Proceeding of the 33rd international ACM SIGIR conference on Research and development in information retrieval.2010:106-113.
[18] Joachims T, Granka L, Pan B, et al. Accurately interpreting clickthrough data as implicit feedback[C]//Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval.2005:154-161.
[19] Agichtein E, Brill E, Dumais S. Improving web search ranking by incorporating user behavior information[C]//Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval.2006:19-26.
[20] Ciaramita M, Murdock V, Plachouras V. Online learning from click data for sponsored search[C]//Proceeding of the 17th international conference on World Wide Web.2008:227-236.
[21] Richardson M, Dominowska E, Ragno R. Predicting clicks: estimating the click-through rate for new ads[C]//Proceedings of the 16th international conference on World Wide Web.2007:521-530.
[22] Shaparenko B, etin , Iyer R. Data-driven text features for sponsored search click prediction[C]//Proceedings of the Third International Workshop on Data Mining and Audience Intelligence for Advertising.2009:46-54.
[23] Hillard D, Manavoglu E, Raghavan H, et al. The sum of its parts: reducing sparsity in click estimation with query segments[J]. Information Retrieval, 2011:1-22.
[24] Graepel T, Candela J, Borchert T, et al. Web-scale Bayesian click-through rate prediction for sponsored search advertising in Microsofts Bing search engine[C]//Proceedings of the Twenty-Seventh International Conference on Machine Learning (ICML-10).2010:13-20.
[25] Kota N, Agarwal D. Temporal multi-hierarchy smoothing for estimating rates of rare events[C]//Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining.2011:1361-1369.
[26] Rutz O, Bucklin R. A model of individual keyword performance in paid search advertising[OL]. 2007.http://papers.ssrn.com/sol3/papers.cfm?abstract id=1024765.
[27] Becker H, Broder A, Gabrilovich E, et al. What happens after an ad click?: quantifying the impact of landing pages in web advertising[C]//Proceeding of the 18th ACM conference on Information and knowledge management.2009:57-66.
[28] Ghose A, Yang S. An empirical analysis of sponsored search performance in search engine advertising[C]//Proceedings of the international conference on Web search and web data mining. 2008:241-250.
[29] Choi Y, Fontoura M, Gabrilovich E, et al. Using landing pages for sponsored search ad selection[C]//Proceedings of the 19th international conference on World wide web. 2010:251-260.
[30] Zhu Y, Wilbur K. Hybrid Advertising Auctions[J]. Marketing Science, 2011, 30(2):249-273.
[31] Agarwal N, Athey S, Yang D. Skewed bidding in pay-per-action auctions for online advertising[J].American Economic Review Papers and Proceedings.2009,99:441-447.
[32] Guo Q, Agichtein E. Ready to buy or just browsing?: detecting web searcher goals from interaction data[C]//Proceeding of the 33rd international ACM SIGIR conference on Research and development in information retrieval.2010:130-137.
[33] Hu Y, Shin J, Tang Z. Pricing of Online Advertising: Cost-Per-Click-Through Vs. Cost-Per-Action[C]//Proceedings of System Sciences (HICSS), 2010 43rd Hawaii International Conference.2010: 1-9.
[34] Broder A, Ciaramita M, Fontoura M, et al. To swing or not to swing: Learning when (not) to advertise[C]//Proceeding of the 17th ACM conference on Information and knowledge management.2008:1003-1012.