NDLI: Similarity query processing for probabilistic sets

Content Provider	IEEE Xplore Digital Library
Author	Ming Gao Cheqing Jin Wei Wang Xuemin Lin Aoying Zhou
Copyright Year	2013
Description	Author affiliation: Univ. of New South Wales, Sydney, NSW, Australia (Wei Wang) \|\| Shanghai Key Lab. on trustworthy Comput., East China Normal Univ., Shanghai, China (Ming Gao; Cheqing Jin; Xuemin Lin; Aoying Zhou)
Abstract	Evaluating similarity between sets is a fundamental task in computer science. However, there are many applications in which elements in a set may be uncertain due to various reasons. Existing work on modeling such probabilistic sets and computing their similarities suffers from huge model sizes or significant similarity evaluation cost, and hence is only applicable to small probabilistic sets. In this paper, we propose a simple yet expressive model that supports many applications where one probabilistic set may have thousands of elements. We define two types of similarities between two probabilistic sets using the possible world semantics; they complement each other in capturing the similarity distributions in the cross product of possible worlds. We design efficient dynamic programming-based algorithms to calculate both types of similarities. Novel individual and batch pruning techniques based on upper bounding the similarity values are also proposed. To accommodate extremely large probabilistic sets, we also design sampling-based approximate query processing methods with strong probabilistic guarantees. We have conducted extensive experiments using both synthetic and real datasets, and demonstrated the effectiveness and efficiency of our proposed methods.
Sponsorship	IEEE Comput. Soc.
Starting Page	913
Ending Page	924
File Size	303599
Page Count	12
File Format	PDF
ISBN	9781467349093
ISSN	10636382
e-ISBN	9781467349109
e-ISBN	9781467349086
DOI	10.1109/ICDE.2013.6544885
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-04-08
Publisher Place	Australia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Probabilistic logic Computational modeling Heuristic algorithms Query processing Approximation algorithms Upper bound Semantics
Content Type	Text
Resource Type	Article

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