Relevance Prediction Challenge / WSDM 2012 Web Search Click Data Workshop

[Pavel Serdyukov <pa...@yandex-team.ru>]

Dear colleagues,

We are pleased to announce the launch of the Relevance Prediction 
Challenge, which is a part of the WSDM 2012 Web Search Click Data (WSCD) 
workshop. This challenge provides a unique opportunity to consolidate 
and scrutinize the work from industrial labs on predicting the relevance 
of URLs using user search behavior. It provides a fully anonymized 
dataset shared by Yandex, which has user queries, clicks on URLs and 
their relevance labels.

Important Dates:
Oct 15, 2011 - Challenge opens
Dec 15, 2011 - End of challenge
Dec 25, 2011 - Winners candidacy notification
Jan 20, 2012 - Reports deadline
Feb 12, 2012 - WSCD workshop at WSDM 2012 
(http://research.microsoft.com/en-us/um/people/nickcr/wscd2012/) and 
Winners announcement

The top three competitors will receive the following cash prizes:

1st place: $5,000
2nd place: $3,000
3rd place: $1,000

Contestants can participate as individuals, or as teams. You will find a 
detailed description of the task, data sets and result evaluation 
methodology at:
http://imat-relpred.yandex.ru/en

Challenge Organizers

Pavel Serdyukov, Eugene Kharitonov, Alexey Gorodilov (Yandex)
Georges Dupret (Yahoo!)
Nick Craswell (Microsoft)

Re: Relevance Prediction Challenge / WSDM 2012 Web Search Click Data Workshop

[Isabel Drost <is...@apache.org>]

On 07.11.2011 Pavel Serdyukov wrote:
> We are pleased to announce the launch of the Relevance Prediction
> Challenge, which is a part of the WSDM 2012 Web Search Click Data (WSCD)
> workshop. This challenge provides a unique opportunity to consolidate
> and scrutinize the work from industrial labs on predicting the relevance
> of URLs using user search behavior. It provides a fully anonymized
> dataset shared by Yandex, which has user queries, clicks on URLs and
> their relevance labels.

Any of our Mahout users interested in taking up that challenge? Might be a nice 
project also for people in the academic world working on relevance models based 
on user feedback.


Isabel