NDLI: Efficient and scalable trie-based algorithms for computing set containment relations

Content Provider	IEEE Xplore Digital Library
Author	Yongming Luo Fletcher, G.H.L. Hidders, J. De Bra, P.
Copyright Year	2015
Description	Author affiliation: Eindhoven Univ. of Technol., Eindhoven, Netherlands (Yongming Luo; Fletcher, G.H.L.; De Bra, P.) \|\| Delft Univ. of Technol., Delft, Netherlands (Hidders, J.)
Abstract	Computing containment relations between massive collections of sets is a fundamental operation in data management, for example in graph analytics and data mining applications. Motivated by recent hardware trends, in this paper we present two novel solutions for computing set-containment joins over massive sets: the Patricia Trie-based Signature Join (PTSJ) and PRETTI+, a Patricia trie enhanced extension of the state-of-the-art PRETTI join. The compact trie structure not only enables efficient use of main-memory, but also significantly boosts the performance of both approaches. By carefully analyzing the algorithms and conducting extensive experiments with various synthetic and real-world datasets, we show that, in many practical cases, our algorithms are an order of magnitude faster than the state-of-the-art.
Starting Page	303
Ending Page	314
File Size	415152
Page Count	12
File Format	PDF
ISBN	9781479979646
DOI	10.1109/ICDE.2015.7113293
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-04-13
Publisher Place	South Korea
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Indexes Data structures Algorithm design and analysis Estimation Data mining Hardware Market research
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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