SIGIR-05 Workshop on
Predicting Query Difficulty - Methods and Applications
Salvador - Bahia - Brazil
August 19, 2005
http://www.haifa.il.ibm.com/sigir05-qp/

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Estimation of query difficulty is an attempt to quantify the quality
of results returned by the search system for a query. Ideally, a
system that can predict difficult queries can adapt parameters or
change algorithms to suit the query. Such a system could give feedback
to the user, for example by reporting confidence scores for results,
and report to the system administrator regarding topics which are of
increasing interest to users but are not answered well by the system.

In this workshop we would like to explore techniques for prediction of
and adaptation to query difficulty.  Specifically, we plan to focus
on:

1. What are the reasons that cause a specific query to become difficult for a given system?
2. Prediction methods for query difficulty.
3. Classification of queries and failure modes, with an eye toward predicting difficulty and suggesting solutions.
4. Evaluation methodology for query prediction.
5. Potential applications for query prediction.
6. Tools and techniques for analysis of retrieval results and failure modes.

Submission Information

        Send by email to David Carmel carmel@il.ibm.com or to Ian
        Soboroff ian.soboroff@nist.gov

For presentation:

        A short vita and a position paper. Length should be no more
        than 2000 words (Postscript or PDF format).  Final versions
        should be submitted in PDF or Postscript for the printed
        version of the workshop materials.  

For participation only:

        A statement of interest, not to exceed 500 words.

Important Dates

   1. Submission: May 15, 2005
   2. Notification: July 01, 2005
   3. Final version: July 22, 2005
   4. SIGIR technical conference: August 15-18, 2005
   5. SIGIR workshop: August 19, 2005


Workshop Organizers:

    * David Carmel, IBM Research Lab in Haifa
    * Ian Soboroff, NIST, USA


Program Committee Members:

    * Gianni Amati, Fondazione Ugo Bordoni
    * Steve Cronen-Townsend, University of Massachusetts
    * Kui-Lam Kwok, City University of NewYork
    * Iadh Ounis,   University of Glasgow
    * Ellen Voorhees, NIST, USA
    * Elad Yom-Tov, IBM Research Lab in Haifa