The ABR wave forms of 16-day-old and adult Mongolian gerbils were evoked by click stimuli presented at rates ranging from 1 to 80/sec. Wave I and wave IV thresholds were determined for each of 5 click rates. Amplitudes and latencies of waves I and IV were measured at each of 7 click rates and 3 intensity levels (15, 40 and 65 dB above threshold). Thresholds for waves I and IV in the adult gerbi...

This paper proposes HNN, a holistic neural network structure for click-through rate (CTR) prediction in recommender systems. Empirically, equipped with HNN, the performance of deep neural networks for CTR prediction are improved on Criteo and Huawei App Store datasets.

A fundamental problem in sponsored search advertising is the estimation of probability of click for ads displayed in response to search queries. The historical click-through rate (CTR) is one of the most important predictors of the click, and extracted at multiple resolutions of the query-ad hierarchy. However, the new ads do not have any click history, and even the existing ads might miss hist...

It is widely believed that the value of acquiring a slot in a sponsored search list (that comes along with the organic links in a search engine’s result page) highly depends on who else is shown in the other sponsored positions. To capture such externality effects, we consider a model of keyword advertising where bidders participate in a Generalized Second Price (GSP) auction and users perform ...

Purpose: The paper looks at how different categories of keywords used in paid placement campaigns influence the click through rate of potential searchers. Design/ Methodology: The paper analyses data from a online travel agency based in Thailand and considers over 5000 keywords for analysis. Findings: The predominant influence of the average position achieved by a keyword in a paid placement ca...

We review a method for click-through rate prediction based on the work of Menon et al. [11], which combines collaborative filtering and matrix factorization with a side-information model and fuses the outputs to proper probabilities in [0, 1]. In addition we provide details, both for the modeling as well as the experimental part, that are not found elsewhere. We rigorously test the performance ...

Suppose an ad network decides that a given click-through is invalid (or “fraudulent”). The implication is that the ad network will not bill the advertiser for that click-through. On the other hand, if the ad network decides that the click-through was valid, they could charge full price. Therefore, arguably, the ad network is “leaving money on the table” by marking click-throughs invalid. As suc...