In sponsored search advertising advertisers bid ad links pertaining to a keyword from search engines. This paper presents a pricing model for sponsored search advertising in a dynamic framework. It focuses on the generalized second-price auction, which is widely used by major search engines including Google and Yahoo!. Unlike the assertion in the literature that the number of advertisers and th...

In pay-per click sponsored search auctions which are currently extensively used by search engines, the auction for a keyword involves a certain number of advertisers (say k) competing for available slots (say m) to display their ads. This auction is typically conducted for a number of rounds (say T ). There are click probabilities μij associated with each agent-slot pairs. The goal of the searc...

Motivated by the recently proposed (and eventually abandoned) partnership in sponsored search advertising between Yahoo! and Google, we examine a model for ad selection in which an agent must balance directly learning which ads perform best and outsourcing ad slots to another party in exchange for a share of any click revenue. Our framework captures a fundamental tension between the potential s...

A unique aspect of sponsored search advertising is that it allows firms to track what products consumers initially search for and what products they eventually buy after visiting their website – something that is typically hard to acquire in physical world settings. Based on a unique dataset that contains information on what keyword advertisements induced consumers to arrive on a firm’s website...

The original analysis of sponsored search auctions by Varian and independently by Aggarwal et al. did not take into account the notion of reserve prices, which are common across all major search engines. We investigate this further and show that the separability assumption derived by Aggarwal et al. is not sufficient for aligning the greedy allocation employed by GSP and the efficient allocatio...

In this paper, we report our approach of KDD Cup 2012 track 2 to predicting the click-through rate (CTR) of advertisements. To accurately predict the CTR of an ad is important for commercial search engine companies for deciding the click prices and the order of impressions. We first implemented three existing methods including Online Bayesian Probit Regression (BPR), Support Vector Machine (SVM...

Click models are an important tool for leveraging user feedback, and are used by commercial search engines for surfacing relevant search results. However, existing click models are lacking in two aspects. First, they do not share information across search results when computing attractiveness. Second, they assume that users interact with the search results sequentially. Based on our analysis of...