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Index Maintenance for Time-Travel Text Search

MPG-Autoren
http://pubman.mpdl.mpg.de/cone/persons/resource/persons44012

Anand,  Avishek
Databases and Information Systems, MPI for Informatics, Max Planck Society;
International Max Planck Research School, MPI for Informatics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons44104

Bedathur,  Srikanta
Databases and Information Systems, MPI for Informatics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons44119

Berberich,  Klaus
Databases and Information Systems, MPI for Informatics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons45380

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

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Zitation

Anand, A., Bedathur, S., Berberich, K., & Schenkel, R. (2012). Index Maintenance for Time-Travel Text Search. In J. Callan, W. Hersh, Y. Maarek, & M. Sanderson (Eds.), SIGIR'12 (pp. 235-244). New York, NY: ACM.


Zitierlink: http://hdl.handle.net/11858/00-001M-0000-0014-59CF-5
Zusammenfassung
Time-travel text search enriches standard text search by temporal predicates, so that users of web archives can easily retrieve document versions that are considered relevant to a given keyword query and existed during a given time interval. Different index structures have been proposed to effciently support time-travel text search. None of them, however, can easily be updated as the Web evolves and new document versions are added to the web archive. In this work, we describe a novel index structure that effciently supports time-travel text search and can be maintained incrementally as new document versions are added to the web archive. Our solution uses a sharded index organization, bounds the number of spuriously read index entries per shard, and can be maintained using small in-memory buffers and append-only operations. We present experiments on two large-scale real-world datasets demonstrating that maintaining our novel index structure is an order of magnitude more efficient than periodically rebuilding one of the existing index structures, while query-processing performance is not adversely affected.