Sponsored search accounts for 40% of the total online advertising market. These ads appear as ordered lists along with the organic (regular) search results in search engine results pages. There is conflicting evidence regarding the impact of organic search results on the sponsored search especially when there is an overlap in the results. We evaluate the impact of advertiser’s link as well as t...

Firms use different attribution strategies such as last-click attribution or first-click attribution to assign conversion credits to search keywords that appear in their consumers’ paths to purchase. These attributed credits impact a firm’s future bidding and budget allocations among keywords and, in turn, determine the overall return-on-investment of search campaigns. In this paper, we model t...

Firms use different attribution strategies such as last-click attribution or first-click attribution to assign conversion credits to search keywords that appear in their consumers’ paths to purchase. These attributed credits impact a firm’s future bidding and budget allocations among keywords and, in turn, determine the overall return-on-investment of search campaigns. In this paper, we model t...

Article in the web is usually titled with a misleading title to attract the users click for gaining click-through rate (CTR). A clickbait title may increase click-through rate, but decrease user experience. Thus, it is important to identify the articles with a misleading title and block them for specific users. Existing methods just consider text features, which hardly produce a satisfactory re...

In this paper, we explore how the contextual ambiguity of a search can affect a keyword's performance. We propose an automatic way of categorizing keywords and examining keyword contextual ambiguity based on topic models from machine learning and computational linguistics. We quantify the effect of contextual ambiguity on keyword click-through performance using a hierarchical Bayesian model, an...

A click on an item is arguably the most widely used feature in recommender systems. However, a click is one out of 174 events a browser can trigger. This paper presents a framework to effectively collect and store data from event streams. A set of mining methods is provided to extract user engagement features such as: attention span, scrolling depth and visible impressions. In this work, we pre...

In paid search advertising on Internet, advertisers bid for specific keywords. Consumer involvement affects a consumer’s purchase intention. However, there has been no research on selecting keywords in paid search advertising depending on consumer involvement from the advertisers’ perspective. Our paper investigates the effects of several factors including impressions, click-through rate, conve...

Click-through rate (CTR) prediction can provide considerable economic and social benefits. Few studies have considered the importance of low-order features, usually employing a simple feature interaction method. To address these issues, we propose novel model called Senet extreme deep field-embedded factorization machine (Se-xDFEFM) for more effective CTR prediction. We first embed squeeze-exci...