Efficient and self-tuning incremental query expansion for top-k query processing

  title={Efficient and self-tuning incremental query expansion for top-k query processing},
  author={Martin Theobald and Ralf Schenkel and Gerhard Weikum},
We present a novel approach for efficient and self-tuning query expansion that is embedded into a top-k query processor with candidate pruning. Traditional query expansion methods select expansion terms whose thematic similarity to the original query terms is above some specified threshold, thus generating a disjunctive query with much higher dimensionality. This poses three major problems: 1) the need for hand-tuning the expansion threshold, 2) the potential topic dilution with overly… CONTINUE READING
Highly Cited
This paper has 83 citations. REVIEW CITATIONS


Publications citing this paper.

84 Citations

Citations per Year
Semantic Scholar estimates that this publication has 84 citations based on the available data.

See our FAQ for additional information.


Publications referenced by this paper.
Showing 1-5 of 5 references

TREC2004 Robust Track Experiments using PIRCS, TREC

K. L. Kwok
View 4 Excerpts
Highly Influenced

Optimal aggregation algorithms for middleware

J. Comput. Syst. Sci. • 2003
View 4 Excerpts
Highly Influenced

Similar Papers

Loading similar papers…