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Interaction of query evaluation and buffer management for information retrieval
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Source International Conference on Management of Data archive
Proceedings of the 1998 ACM SIGMOD international conference on Management of data table of contents
Seattle, Washington, United States
Pages: 118 - 129  
Year of Publication: 1998
ISBN:0-89791-995-5
Also published in ...
Authors
Björn T. Jónsson  University of Maryland
Michael J. Franklin  University of Maryland
Divesh Srivastava  AT&T Labs-Research
Sponsors
SIGACT: ACM Special Interest Group on Algorithms and Computation Theory
SIGART: ACM Special Interest Group on Artificial Intelligence
SIGMOD: ACM Special Interest Group on Management of Data
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 4,   Downloads (12 Months): 38,   Citation Count: 11
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ABSTRACT

The proliferation of the World Wide Web has brought information retrieval (IR) techniques to the forefront of search technology. To the average computer user, “searching” now means using IR-based systems for finding information on the WWW or in other document collections. IR query evaluation methods and workloads differ significantly from those found in database systems. In this paper, we focus on three such differences. First, due to the inherent fuzziness of the natural language used in IR queries and documents, an additional degree of flexibility is permitted in evaluating queries. Second, IR query evaluation algorithms tend to have access patterns that cause problems for traditional buffer replacement policies. Third, IR search is often an iterative process, in which a query is repeatedly refined and resubmitted by the user. Based on these differences, we develop two complementary techniques to improve the efficiency of IR queries: 1) Buffer-aware query evaluation, which alters the query evaluation process based on the current contents of buffers; and 2) Ranking-aware buffer replacement, which incorporates knowledge of the query processing strategy into replacement decisions. In a detailed performance study we show that using either of these techniques yields significant performance benefits and that in many cases, combining them produces even further improvements.


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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CITED BY  11

Collaborative Colleagues:
Björn T. Jónsson: colleagues
Michael J. Franklin: colleagues
Divesh Srivastava: colleagues