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Modeling and Managing Content Changes in Text Databases (2007)
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BibTeX
@MISC{Ipeirotis07modelingand,
author = {Panagiotis G. Ipeirotis and Alexandros Ntoulas and Junghoo Cho and Luis Gravano},
title = {Modeling and Managing Content Changes in Text Databases},
year = {2007}
}
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Abstract
Large amounts of (often valuable) information are stored in web-accessible text databases. “Metasearchers” provide unified interfaces to query multiple such databases at once. For efficiency, metasearchers rely on succinct statistical summaries of the database contents to select the best databases for each query. So far, database selection research has largely assumed that databases are static, so the associated statistical summaries do not evolve over time. However, databases are rarely static and the statistical summaries that describe their contents need to be updated periodically to reflect content changes. In this article, we first report the results of a study showing how the content summaries of 152 real web databases evolved over a period of 52 weeks. Then, we show how to use “survival analysis ” techniques in general, and Cox’s proportional hazards regression in particular, to model database changes over time and predict when we should update each content summary. Finally, we exploit our change model to devise update schedules that keep the summaries up to date by contacting databases only when needed, and then we evaluate the
Keyphrases
text database managing content change content summary update schedule change model unified interface associated statistical summary content change real web database database selection research web-accessible text database succinct statistical summary database change database content statistical summary large amount multiple database proportional hazard regression survival analysis technique
