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  Efficient Temporal Keyword Queries over Versioned Text

Anand, A., Bedathur, S., Berberich, K., & Schenkel, R. (2010). Efficient Temporal Keyword Queries over Versioned Text. In X. J. Huang, G. Jones, N. Koudas, X. Wu, & K. Collins-Thompson (Eds.), Proceedings of the 19th ACM Conference on Information and Knowledge Management (pp. 699-708). New York, NY: ACM. doi:10.1145/1871437.1871528.

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Item Permalink: https://hdl.handle.net/11858/00-001M-0000-000F-14E4-B Version Permalink: https://hdl.handle.net/11858/00-001M-0000-0024-33F7-2
Genre: Conference Paper

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 Creators:
Anand, Avishek1, Author           
Bedathur, Srikanta1, Author           
Berberich, Klaus1, Author           
Schenkel, Ralf1, Author           
Affiliations:
1Databases and Information Systems, MPI for Informatics, Max Planck Society, ou_24018              

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 Abstract: Modern text analytics applications operate on large volumes of temporal text data such as Web archives, newspaper archives, blogs, wikis, and micro-blogs. In these settings, searching and mining needs to use constraints on the time dimension in addition to keyword constraints. A natural approach to address such queries is using an inverted index whose entries are enriched with valid-time intervals. It has been shown that these indexes have to be partitioned along time in order to achieve efficiency. However, when the temporal predicate corresponds to a long time range, requiring the processing of multiple partitions, naive query processing incurs high cost of reading of redundant entries across partitions. We present a framework for efficient approximate processing of keyword queries over a temporally partitioned inverted index which minimizes this overhead, thus speeding up query processing. By using a small synopsis for each partition we identify partitions that maximize the number of final non-redundant results, and schedule them for processing early on. Our approach aims to balance the estimated gains in the final result recall against the cost of index reading required. We present practical algorithms for the resulting optimization problem of index partition selection. Our experiments with three diverse, large-scale text archives reveal that our proposed approach can provide close to 80\% result recall even when only about half the index is allowed to be read.

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Language(s): eng - English
 Dates: 20102010
 Publication Status: Issued
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: eDoc: 536378
DOI: 10.1145/1871437.1871528
URI: http://doi.acm.org/10.1145/1871437.1871528
Other: Local-ID: C1256DBF005F876D-63EEA22E6EFA1620C12577840044D36B-AnandBBS_CIKM10
 Degree: -

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Title: 19th ACM Conference on Information and Knowledge Management
Place of Event: Toronto, Canada
Start-/End Date: 2010-10-26 - 2010-10-30

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Title: Proceedings of the 19th ACM Conference on Information and Knowledge Management
  Abbreviation : CIKM 2010
Source Genre: Proceedings
 Creator(s):
Huang, Xiangji Jimmy1, Editor
Jones, Gareth1, Editor
Koudas, Nick1, Editor
Wu, Xindong1, Editor
Collins-Thompson, Kevyn1, Editor
Affiliations:
1 External Organizations, ou_persistent22            
Publ. Info: New York, NY : ACM
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 699 - 708 Identifier: ISBN: 978-1-4503-0099-5