Incorporating Non-Relevance Information in the Estimation of Query Models

TREC

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.

  • [PDF] 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}}

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