Motivation
The attraction of hundreds of millions of web searches per day provides significant incentive for many content providers to do whatever is necessary to rank highly in search engine results, while search engine providers want to provide the most accurate results. The conflicting goals of search and content providers is adversarial, and the use of techniques that push rankings higher than they belong is often called search engine spam. Such methods typically include textual as well as link-based techniques, or their combination.
Work in search engine spam has been scattered across many venues. This workshop provides a focused venue for both mature and early-stage work in web-based adversarial IR.
This workshop brings together researchers and industry practitioners and will provide participants with a survey of current problems in adversarial Web IR and state-of-the-art research advances to address them. In addition, the workshop will present the opportunity to identify datasets, determine evaluation methodologies, evoke more general theories of what the adversarial process will entail, and gather feedback from commercial participants on how research in this area can contribute to practice.
Topics
Workshop areas of interest include, but are not limited to:- search engine spam and optimization,
- crawling the web without detection,
- link-bombing (a.k.a. Google-bombing),
- comment spam, referrer spam,
- blog spam (splogs),
- malicious tagging,
- reverse engineering of ranking algorithms,
- advertisement blocking, and
- web content filtering.
Papers addressing higher-level concerns (e.g., whether ′open′ algorithms can succeed in an adversarial environment, whether permanent solutions are possible, etc.) are also welcome.
Call for Papers
This, the second AIRWeb workshop, builds on last year′s successful meeting in Chiba, Japan as part of WWW2005. This year we solicit both full and short submissions on any aspect of adversarial information retrieval on the Web.
Full papers are limited to 8 pages in the standard ACM SIGIR format (except please include author information -- we are not operating double-blind reviews); works-in-progress will be permitted 4 pages, including all figures and references. Papers should be submitted, in PDF form, to airweb(at)cse.lehigh.edu by the submission deadline.
At least three anonymous reviews will be provided per paper, judged on the usual basis of relevance, originality, quality, and presentation. Proceedings of the workshop will be placed online, and distributed at the workshop. A selection of best papers will be invited to submit expanded versions to an appropriate journal. 数据挖掘研究院
We also have a text version of the Call for Papers that is suitable for e-mail distribution.
Organizing Committee
- Tim Converse, Yahoo! Search
- Brian D. Davison, Lehigh University
- Marc Najork, Microsoft Research
Program Committee
- Sibel Adali, Rensselaer Polytechnic Institute, USA
- Lada Adamic, University of Michigan, USA
- Einat Amitay, IBM Research Haifa, Israel
- Andrei Broder, Yahoo! Research, USA
- Carlos Castillo, Universita di Roma "La Sapienza", Italy
- Abdur Chowdhury, AOL Search, USA
- Nick Craswell, Microsoft Research Cambridge, UK
- Matt Cutts, Google, USA
- Dennis Fetterly, Microsoft Research, USA
- Zoltan Gyongyi, Stanford University, USA
- Matthew Hurst, BuzzMetrics, USA
- Mark Manasse, Microsoft Research, USA
- Jan Pedersen, Yahoo!, USA
- Bernhard Seefeld, Switzerland
- Erik Selberg, Microsoft Search, USA
- Andrew Tomkins, Yahoo! Research, USA
- Tao Yang, Ask.com/Univ. of California-Santa Barbara, USA
Contact Email
- airweb(at)cse.lehigh.edu
