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ADKDD '08: Proceedings of the 2nd International Workshop on Data Mining and Audience Intelligence for Advertising
ACM2008 Proceeding
Publisher:
  • Association for Computing Machinery
  • New York
  • NY
  • United States
Conference:
KDD08: The 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining Las Vegas Nevada 24 August 2008
ISBN:
978-1-60558-277-1
Published:
24 August 2008
Sponsors:
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Abstract

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.

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research-article
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, ...

research-article
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 ...

research-article
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 ...

research-article
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 ...

research-article
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 ...

research-article
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 ...

research-article
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 ...

Contributors
  • Microsoft Corporation
  • Microsoft Research
  1. Proceedings of the 2nd International Workshop on Data Mining and Audience Intelligence for Advertising

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    Acceptance Rates

    Overall Acceptance Rate 12 of 21 submissions, 57%
    YearSubmittedAcceptedRate
    ADKDD'17211257%
    Overall211257%