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Static score bucketing in inverted indexes
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Source Conference on Information and Knowledge Management archive
Proceedings of the 14th ACM international conference on Information and knowledge management table of contents
Bremen, Germany
POSTER SESSION: Poster Session table of contents
Pages: 311 - 312  
Year of Publication: 2005
ISBN:1-59593-140-6
Authors
Chavdar Botev  Cornell University, Ithaca, NY
Nadav Eiron  IBM Almaden Research Center, San Jose, CA
Marcus Fontoura  IBM Almaden Research Center, San Jose, CA
Ning Li  IBM Almaden Research Center, San Jose, CA
Eugene Shekita  IBM Almaden Research Center, San Jose, CA
Sponsors
ACM: Association for Computing Machinery
SIGIR: ACM Special Interest Group on Information Retrieval
Publisher
ACM  New York, NY, USA
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ABSTRACT

Maintaining strict static score order of inverted lists is a heuristic used by search engines to improve the quality of query results when the entire inverted lists cannot be processed. This heuristic, however, increases the cost of index generation and requires complex index build algorithms. In this paper, we study a new index organization based on static score bucketing. We show that this new technique significantly improves in index build performance while having minimal impact on the quality of search results.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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M. Fontoura, A. Neumann, S. Rajagopalan, E. Shekita, and J. Zien. High performance index build algorithms for intranet search engines. In VLDB' 2004.
 
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T. Haveliwala. Efficient encoding for document ranking vectors. In Proc. of 4th Int. Conference on Internet Computing, 2003.
 
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X. Long and T. Suel. Optimized query execution in large search engines with global page ordering. In Proc. of the 29th Int. Conf. on Very Large Databases, 2003.

Collaborative Colleagues:
Chavdar Botev: colleagues
Nadav Eiron: colleagues
Marcus Fontoura: colleagues
Ning Li: colleagues
Eugene Shekita: colleagues