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SIGIR 2011 Previews

Accepted SIGIR 2011 authors have started posting their papers online, so I have decided to collect them here.  Please comment on the ones you think are the most interesting and important.  As I get more papers, I’ll edit this post to add them. http://bit.ly/kMWe1b Lidan Wang, Jimmy Lin, and Don Metzler, “A Cascade Ranking Model for […] → Read More: SIGIR 2011 Previews

Vote for the best CIKM 2010 papers

CIKM 2010 is taking place right now in Toronto, Ontario, Canada.  I have collected all the papers in the IR track below.  Please take a moment to vote for those papers you think are the most provocative, innovative, startling, or otherwise interesting.  You can vote for up to 3 papers. I had to make a […] → Read More: Vote for the best CIKM 2010 papers

Vote for the best CIKM 2010 papers

CIKM 2010 is taking place right now in Toronto, Ontario, Canada.  I have collected all the papers in the IR track below.  Please take a moment to vote for those papers you think are the most provocative, innovative, startling, or otherwise interesting.  You can vote for up to 3 papers. I had to make a […] → Read More: Vote for the best CIKM 2010 papers

Vote for the best CIKM 2010 papers

CIKM 2010 is taking place right now in Toronto, Ontario, Canada.  I have collected all the papers in the IR track below.  Please take a moment to vote for those papers you think are the most provocative, innovative, startling, or otherwise interesting.  You can vote for up to 3 papers. I had to make a […] → Read More: Vote for the best CIKM 2010 papers

Vote for the best CIKM 2010 papers

CIKM 2010 is taking place right now in Toronto, Ontario, Canada.  I have collected all the papers in the IR track below.  Please take a moment to vote for those papers you think are the most provocative, innovative, startling, or otherwise interesting.  You can vote for up to 3 papers. I had to make a […] → Read More: Vote for the best CIKM 2010 papers

Vote for the best CIKM 2010 papers

CIKM 2010 is taking place right now in Toronto, Ontario, Canada.  I have collected all the papers in the IR track below.  Please take a moment to vote for those papers you think are the most provocative, innovative, startling, or otherwise interesting.  You can vote for up to 3 papers. I had to make a […] → Read More: Vote for the best CIKM 2010 papers

Vote for the best CIKM 2010 papers

CIKM 2010 is taking place right now in Toronto, Ontario, Canada.  I have collected all the papers in the IR track below.  Please take a moment to vote for those papers you think are the most provocative, innovative, startling, or otherwise interesting.  You can vote for up to 3 papers. I had to make a […] → Read More: Vote for the best CIKM 2010 papers

Vote for the best CIKM 2010 papers

CIKM 2010 is taking place right now in Toronto, Ontario, Canada.  I have collected all the papers in the IR track below.  Please take a moment to vote for those papers you think are the most provocative, innovative, startling, or otherwise interesting.  You can vote for up to 3 papers. I had to make a […] → Read More: Vote for the best CIKM 2010 papers

Efficient and Effective Spam Filtering and Re-ranking for Large Web Datasets

Gordon V. Cormack, Mark D. Smucker, and Charles L. A. Clarke University of Waterloo The TREC 2009 web ad hoc and relevance feedback tasks used a new document collection, the ClueWeb09 dataset, which was crawled from the general Web in early 2009. This dataset contains 1 billion web pages, a substantial fraction of which are […] → Read More: Efficient and Effective Spam Filtering and Re-ranking for Large Web Datasets

Efficient and Effective Spam Filtering and Re-ranking for Large Web Datasets

Gordon V. Cormack, Mark D. Smucker, and Charles L. A. Clarke University of Waterloo The TREC 2009 web ad hoc and relevance feedback tasks used a new document collection, the ClueWeb09 dataset, which was crawled from the general Web in early 2009. This dataset contains 1 billion web pages, a substantial fraction of which are […] → Read More: Efficient and Effective Spam Filtering and Re-ranking for Large Web Datasets