Global advertising is projected to exceed half-a-trillion dollars by the year 2010. Although online advertising is currently only a small part of this large enterprise, it is growing at a rapid pace. The explosion in the number of participants in the online advertising marketplace has generated large volumes of data and exciting data mining problems. Earlier research on search logs, web pages, social network and blogs had focused on information organization, retrieval and understanding. Recently there has been strong research interest in the advertisement angle to all these information sources.
Researchers have tackled several challenging problems on online monetization like sponsored search, contextual advertising for web pages, understanding user intent and user demographics for advertisements, mining user reviews for product pricing, predicting click-through rates for ads, just to name a few. Further, the on-line and offline advertising worlds are fast converging; for example, digital marketplaces are migrating from the online world to TV and radio, and audience understanding work from offline media is trickling into the online realm. Since data mining researchers and practitioners in all these areas come from different communities, there is strong need for a single forum to bring together people involved in all aspects of digital advertising. We are addressing this need with the Workshop on Data Mining and Audience Intelligence for Advertising.
The goal of this workshop is to not only increase communication between researchers working on seemingly different pieces of the advertisement pie, but to encourage data mining researchers to bring new ideas from related areas to solve the numerous challenges faced by the rapidly changing digital advertising industry. We want to bring together auction theorists, social network researchers, natural language researchers, information retrieval experts, audience understanding researchers, television advertisement analysts and many others, to promote a fruitful exchange of ideas to advance the field.
Proceeding Downloads
An empirical analysis of return on investment maximization in sponsored search auctions
We empirically investigate whether advertisers are maximizing their return on investment (ROI) across multiple keywords in sponsored search auctions. Because testing for ROI maximization relies on knowledge of advertisers' private true values per click, ...
Online effects of offline ads
We propose a methodology for assessing how ad campaigns in offline media such as print, audio and TV affect online interest in the advertiser's brand. Online interest can be measured by daily counts of the number of search queries that contain brand ...
Comparing performance metrics in organic search with sponsored search advertising
With the rapid growth of search advertising, there has been an increased interest amongst both practitioners and academics in enhancing our understanding of how consumers respond to contextual and sponsored search advertising on the Internet. An ...
An algorithm for analyzing personalized online commercial intention
With more and more commercial activities moving onto the Internet, people tend to purchase what they need through Internet or conduct some online research before the actual deals happen. For many Web users, their online commercial activities start from ...
Consistent phrase relevance measures
Measuring the relevance between a document and a phrase is fundamental to many information retrieval and matching tasks including on-line advertising. In this paper, we explore two approaches for measuring the relevance between a document and a phrase ...
Variable selection for ad prediction
We consider the problem of predicting the probability of a click for an advertisement when the outcome of a click or no-click is expressed by means of a set of a large number of variables. Many, if not most, of these variables are very weakly related to ...
Sponsored ad-based similarity: an approach to mining collective advertiser intelligence
We present a method for mining the intelligence of advertisers to detect product similarities and generate accurate recommendations. In contrast to conventional recommendation algorithms, our approach is completely automated and relies solely on ...
- Proceedings of the 2nd International Workshop on Data Mining and Audience Intelligence for Advertising
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Data mining and audience intelligence for advertising
Special issue on visual analyticsGrowth in the global advertising industry - especially the recent rapid growth in online advertising - has generated large volumes of data, bringing along with it many challenging data mining problems. Researchers from various disciplines have brought ...
Acceptance Rates
Year | Submitted | Accepted | Rate |
---|---|---|---|
ADKDD'17 | 21 | 12 | 57% |
Overall | 21 | 12 | 57% |