Incorporating Non-Relevance Information in the Estimation of Query Models

We describe the participation of the University of Amsterdam’s ILPS group in the relevance feedback track at TREC 2008. We introduce a new model which incorporates information from relevant and non-relevant documents to improve the estimation of query models. Our main findings are twofold: (i) in terms of statMAP, a larger number of judged non-relevant documents improves retrieval effectiveness and (ii) on the TREC Ter- abyte topics, we can effectively replace the estimates on the judged non-relevant documents with estimations on the document collection.

• E. Meij, W. Weerkamp, J. He, and M. de Rijke, “Incorporating non-relevance information in the estimation of query models,” in The seventeenth text retrieval conference, 2009.
  [Bibtex]

  @inproceedings{TREC:2009:meij,
  Abstract = {We describe the participation of the University of Amsterdam's ILPS group in the relevance feedback track at TREC 2008. We introduce a new model which incorporates information from relevant and non-relevant documents to improve the estimation of query models. Our main findings are twofold: (i) in terms of statMAP, a larger number of judged non-relevant documents improves retrieval effectiveness and (ii) on the TREC Terabyte topics, we can effectively replace the estimates on the judged non-relevant documents with estimations on the document collection.},
  Author = {Meij, E. and Weerkamp, W. and He, J. and de Rijke, M.},
  Booktitle = {The Seventeenth Text REtrieval Conference},
  Date-Added = {2011-10-16 16:03:56 +0200},
  Date-Modified = {2012-10-30 09:23:32 +0000},
  Series = {TREC 2008},
  Title = {Incorporating Non-Relevance Information in the Estimation of Query Models},
  Year = {2009}}