2007 Proceeding- General Chair:
- Ying Li
Global advertising is a half-a-trillion dollar a year business. Although online advertising is currently a small part of this enterprise, it is rapidly growing. The explosion in the number of participants in online advertising marketplaces, and other online entities such as blogs and social networks, has generated large volumes of data and exciting data mining problems. Earlier research on these online entities has focused on information organization, retrieval and understanding. Recently there is increased research interest in the advertisement angle to all these avenues also. 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. Hence there is strong need for a single forum to bring together researchers and practitioners who are involved in all aspects of digital advertising. We are addressing this need with the First Workshop on Data Mining and Audience Intelligence for Advertising.
The goal of this workshop is to encourage data mining researchers to take on the numerous challenges faced by the rapidly changing digital advertising industry, and to increase communication between researchers working on seemingly different pieces of the advertisement pie. 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
Pay-per-action model for online advertising
The online advertising industry is currently based on two dominant business models: the pay-per-impression model and the pay-per-click model. With the growth of sponsored search during the last few years, there has been a move toward the pay-per-click ...
More bang for their bucks: assessing new features for online advertisers
Online search systems that display ads continually offer new features that advertisers can use to fine-tune and enhance their ad campaigns. An important question is whether a new feature actually helps advertisers. In an ideal world for statisticians, ...
The economics of attention: maximizing user value in information-rich environments
We introduce an automatic configuration mechanism that generates the most relevant information to be presented to limited attention users of information-rich media. It also guarantees to maximize their total expected utility from the information they ...
A noisy-channel approach to contextual advertising
Contextual advertising is a growing category of search advertising. It presents a particular challenge to ad placement systems because of the sparseness of the language of advertising. We present a system that is language independent and knowledge free ...
Sensitive webpage classification for content advertising
Online advertising has been a popular topic in recent years. In this paper, we address one of the important problems in online advertising, i.e., how to detect whether a publisher webpage contains sensitive content and is appropriate for showing ...
Sentiment classification with interpolated information diffusion kernels
Information diffusion kernels - similarity metrics in non-Euclidean information spaces - have been found to produce state of the art results for document classification. In this paper, we present a novel approach to global sentiment classification using ...
Extracting opinion topics for Chinese opinions using dependence grammar
Previous work on opinion/sentiment mining focuses only on sentiment classification with the postulation that topics are identified a prior. However, this assumption often fails in reality. In advertising, topics on which users are commenting are crucial ...
Discovering information diffusion paths from blogosphere for online advertising
Allowing global distribution of information to large audiences at very low cost, the Internet has emerged as a vital medium for marketing and advertising. Weblogs, a new form of self publication on the Internet, have attracted online advertisers because ...
Finding keyword from online broadcasting content for targeted advertising
Content targeted advertising has been a successful way of delivering ads, as effective technologies were developed to find keywords from the webpage a user is browsing. However, existing technologies cannot be easily applied to find keywords from online ...
From TV to online advertising: recent experience from the Spanish media
The advance of the Internet as a competitor with traditional media (radio, TV, newspapers and magazines) is attracting advertisements, but traditional analytical tools for media planning are not directly applicable. In this paper we describe our ...
- Proceedings of the 1st international workshop on Data mining and audience intelligence for advertising
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Data mining and audience intelligence for advertising
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Acceptance Rates
| Year | Submitted | Accepted | Rate |
|---|---|---|---|
| ADKDD'17 | 21 | 12 | 57% |
| Overall | 21 | 12 | 57% |