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Conference Paper

Index Tuning for Efficient Proximity-Enhanced Query Processing

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Broschart,  Andreas
Databases and Information Systems, MPI for Informatics, Max Planck Society;

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Schenkel,  Ralf
Databases and Information Systems, MPI for Informatics, Max Planck Society;

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Citation

Broschart, A., & Schenkel, R. (2009). Index Tuning for Efficient Proximity-Enhanced Query Processing. In S. Geva, J. Kamps, & A. Trotman (Eds.), Pre-proceedings of the 2009 INEX Workshop (pp. 188-191). Amsterdam: IR Publications. Retrieved from http://www.inex.otago.ac.nz/data/proceedings/INEX2009-preproceedings.pdf.


Cite as: https://hdl.handle.net/11858/00-001M-0000-000F-191D-5
Abstract
Scoring models that make use of proximity information usually improve result quality in text retrieval. Considering that index structures carrying proximity information can grow huge in size if they are not pruned, it is helpful to tune indexes towards space requirements and retrieval quality. This paper elaborates on our approach used for INEX 2009 to tune index structures for different choices of result size k. To allow for comparison as to retrieval quality with non-pruned index structures, we also depict our results from the Adhoc Track.