Plot of a query-specific burst

Adaptive Temporal Query Modeling

We present an approach to query modeling that uses the temporal distribution of documents in an initially retrieved set of documents. Such distributions tend to exhibit bursts, especially in news related document collections. We hypothesize that documents in those bursts are more likely to be relevant than others. Predicated on this, we expand queries with the most distinguishing terms in high quality documents sampled from bursts. We show how the most commonly used decay function for recent document retrieval can be used as probabilistic model for temporal retrieval in general. The effectiveness of our models is demonstrated on both news collections and a collection of blog posts.

  • [PDF] M. Peetz, E. Meij, M. de Rijke, and W. Weerkamp, “Adaptive temporal query modeling,” in Advances in information retrieval – 34th european conference on ir research, ecir 2012, 2012.
    [Bibtex]
    @inproceedings{ECIR:2012:peetz,
    Author = {Peetz, Maria-Hendrike and Meij, Edgar and de Rijke, Maarten and Weerkamp, Wouter},
    Booktitle = {Advances in Information Retrieval - 34th European Conference on IR Research, ECIR 2012},
    Date-Added = {2011-11-23 18:10:40 +0100},
    Date-Modified = {2012-10-28 23:01:12 +0000},
    Title = {Adaptive Temporal Query Modeling},
    Year = {2012}}