GrammarViz 2.0: A Tool for Grammar-Based Pattern Discovery in Time Series

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dc.contributor.authorSenin, Pavel
dc.contributor.authorLin, Jessica
dc.contributor.authorWang, Xing
dc.contributor.authorOates, Tim
dc.contributor.authorGandhi, Sunil
dc.contributor.authorBoedihardjo, Arnold P.
dc.contributor.authorChen, Crystal
dc.contributor.authorFrankenstein, Susan
dc.contributor.authorLerner, Manfred
dc.date.accessioned2020-03-04T13:30:56Z
dc.date.available2020-03-04T13:30:56Z
dc.description.abstractThe problem of frequent and anomalous patterns discovery in time series has received a lot of attention in the past decade. Addressing the common limitation of existing techniques, which require a pattern length to be known in advance, we recently proposed grammar-based algorithms for efficient discovery of variable length frequent and rare patterns. In this paper we present GrammarViz2.0, an interactive tool that, based on our previous work, implements algorithms for grammar-driven mining and visualization of variable length time series patterns.en_US
dc.description.urihttps://link.springer.com/chapter/10.1007/978-3-662-44845-8_37#aboutcontenten_US
dc.format.extent5 pagesen_US
dc.genreconference papers and proceedingsen_US
dc.identifierdoi:10.13016/m2pbbk-rlsp
dc.identifier.citationSenin P. et al. (2014) GrammarViz 2.0: A Tool for Grammar-Based Pattern Discovery in Time Series. In: Calders T., Esposito F., Hüllermeier E., Meo R. (eds) Machine Learning and Knowledge Discovery in Databases. ECML PKDD 2014. Lecture Notes in Computer Science, vol 8726. Springer, Berlin, Heidelbergen_US
dc.identifier.urihttps://doi.org/10.1007/978-3-662-44845-8_37
dc.identifier.urihttp://hdl.handle.net/11603/17460
dc.language.isoen_USen_US
dc.publisherSpringeren_US
dc.relation.isAvailableAtThe University of Maryland, Baltimore County (UMBC)
dc.relation.ispartofUMBC Computer Science and Electrical Engineering Department Collection
dc.relation.ispartofUMBC Faculty Collection
dc.relation.ispartofUMBC Student Collection
dc.rightsThis item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author.
dc.rightsPublic Domain Mark 1.0*
dc.rightsThis work was written as part of one of the author's official duties as an Employee of the United States Government and is therefore a work of the United States Government. In accordance with 17 U.S.C. 105, no copyright protection is available for such works under U.S. Law.
dc.rights.urihttp://creativecommons.org/publicdomain/mark/1.0/*
dc.titleGrammarViz 2.0: A Tool for Grammar-Based Pattern Discovery in Time Seriesen_US
dc.typeTexten_US

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