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2008
Springer

SNIF TOOL: sniffing for patterns in continuous streams

9 years 4 days ago
SNIF TOOL: sniffing for patterns in continuous streams
Continuous time-series sequence matching, specifically, matching a numeric live stream against a set of predefined pattern sequences, is critical for domains ranging from fire spread tracking to network traffic monitoring. While several algorithms exist for similarity matching of static time-series data, matching continuous data poses new, largely unsolved challenges including online real-time processing requirements and system resource limitations for handling infinite streams. In this work, we propose a novel live stream matching framework, called n-Snippet Indices Framework (in short, SNIF), to tackle these challenges. SNIF employs snippets as the basic unit for matching streaming time-series. The insight is to perform the matching at two levels of granularity: bag matching of subsets of snippets of the live stream against prefixes of the patterns, and order checking for maintaining successive candidate snippet bag matches. We design a two-level index structure, called SNIF index, ...
Abhishek Mukherji, Elke A. Rundensteiner, David C.
Added 12 Oct 2010
Updated 12 Oct 2010
Type Conference
Year 2008
Where CIKM
Authors Abhishek Mukherji, Elke A. Rundensteiner, David C. Brown, Venkatesh Raghavan
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