CIKM 2009 - Hong Kong, China November 2-6, 2009
 
CIKM 2009 - The 18th ACM Conference on Information and Knowledge Management
The 18th ACM Conference on
Information and Knowledge Management


OVERVIEW

Online advertising is the primary driving force behind many Web activities, including Internet search as well as publishing of online content by third-party providers. A new discipline - Computational Advertising - has recently emerged, which studies the process of advertising on the Internet from a variety of angles. A successful advertising campaign should be relevant to the immediate user's information need as well as more generally to user's background and personalized interest profile, be economically worthwhile to the advertiser and the intermediaries (e.g., the search engine), as well as be aesthetically pleasant and not detrimental to user experience.

The tutorial does not assume any prior knowledge of Web advertising, and will begin with a comprehensive background survey of the topic. In this tutorial, we focus on one important aspect of online advertising, namely, contextual relevance. It is essential to emphasize that in most cases the context of user's actions is defined by a body of text, hence the ad matching problem lends itself to many AI methods. At first approximation, the process of obtaining relevant ads can be reduced to conventional information retrieval, where one constructs a query that describes the user's context, and then executes this query against a large inverted index of ads. We show how to augment the standard information retrieval approach using query expansion and text classification techniques. We demonstrate how to employ a relevance feedback assumption and use Web search results retrieved by the query. This step allows one to use the Web as a repository of relevant query-specific knowledge. We also go beyond the conventional bag of words indexing, and construct additional knowledge-rich features using a large external taxonomy and a lexicon of named entities obtained by analyzing the entire Web as a corpus. Computational advertising poses numerous challenges and open research problems in text summarization, natural language generation, named entity extraction, computer-human interaction, and others. The last part of the tutorial will be devoted to recent research results as well as open problems, such as automatically classifying cases when no ads should be shown, handling geographic names, and context modeling for vertical portals.
Topics

  • Introduction
  • Advertising on the Web
    • The evolution of Web advertising
    • Advertese (introduction of terminology)
    • Main scenarios of online advertising
      • Sponsored search
      • Content match
      • Exact match vs. broad match
    • The economics of Web advertising
  • Main technical challenges for AI, NLP and IR
  • Bibliography survey
  • IR modeling
    • Ads as information supply and reduction to search
    • A unified approach to Web advertising
    • Using search results as external knowledge
    • Text classification
    • Named entities
  • The research frontier
    • Text summarization / just-in-time advertising
    • When not to advertise / ad spam
    • Location awareness / geo-targeting
    • Context modeling
  • Discussion
Instructors

Affiliation: Yahoo! Research, Computational Advertising and Search Technology Group

Short Bios

    Andrei Broder is a Fellow and Vice President for Computational Advertising in Yahoo! Research. He also serves as Chief Scientist of Yahoo’s Advertising Technology Group. Previously he was an IBM Distinguished Engineer and the CTO of the Institute for Search and Text Analysis in IBM Research. From 1999 until 2002 he was Vice President for Research and Chief Scientist at the AltaVista Company. He graduated Summa cum Laude from the Technion, and obtained his M.Sc. and Ph.D. in Computer Science at Stanford University. His current research interests are centered on computational advertising, web search, context-driven information supply, and randomized algorithms.

    Broder is co-winner of the Best Paper award at WWW6 (for his work on duplicate elimination of web pages) and at WWW9 (for his work on mapping the web). He has authored more than ninety papers and was awarded twenty-eight patents. He is an ACM Fellow, an IEEE fellow, and past chair of the IEEE Technical Committee on Mathematical Foundations of Computing.
    http://research.yahoo.com/Andrei_Broder
    Evgeniy Gabrilovich is a Senior Research Scientist at Yahoo! Research. His research interests include information retrieval, machine learning, and computational linguistics. Recently, he co-organized a workshop on the synergy between Wikipedia and research in AI at AAAI 2008, and a workshop on Information Retrieval for Advertising at SIGIR 2008. He also co-presented tutorials on computational advertising at ACL 2008 and EC 2008. He served on the program committees of ACL, AAAI, WWW, CIKM, JCDL, EMNLP, and COLING, as well as reviewed papers for the ACM TOIT, TOIS, TKDE, Journal of Natural Language Engineering (JNLE), and Communications of the ACM. Evgeniy earned his PhD in Computer Science from the Technion - Israel Institute of Technology, where he developed a methodology for using large scale repositories of world knowledge for enhancing text representation beyond the bag of words.
    http://research.yahoo.com/Evgeniy_Gabrilovich
    Vanja Josifovski is a Principal Research Scientist at Yahoo! Research, where he works on search and advertisement technologies for the Internet. He is currently exploring designs for the next generation ad placement platforms for contextual and search advertising. Previously, Vanja was a Research Staff Member at the IBM Almaden Research Center working on several projects in database runtime and optimization, federated databases, and enterprise. He earned his MSc degree from the University of Florida at Gainesville and his PhD from the Linkoping University in Sweden. Vanja published over thirty peer reviewed publications, authored around 20 patent applications, and was on the program committees of WWW, SIGIR, ICDE, VLDB and other major conferences in the database, information retrieval, and search areas.
    http://research.yahoo.com/Vanja_Josifovski