Learning Pattern Graphs for Multivariate Temporal Pattern Retrieval

dc.contributor.authorPeter, Sebastian
dc.contributor.authorHöppner, Frankdeu
dc.contributor.authorBerthold, Michael R.
dc.date.accessioned2013-06-20T09:17:13Zdeu
dc.date.available2013-06-20T09:17:13Zdeu
dc.date.issued2012
dc.description.abstractWe propose a two-phased approach to learn pattern graphs, a powerful pattern language for complex, multivariate temporal data, which is capable of reflecting more aspects of temporal patterns than earlier proposals. The first phase aims at increasing the understandability of the graph by finding common substructures, thereby helping the second phase to specialize the graph learned so far to discriminate against undesired situations. The usefulness is shown on data from the automobile industry and the libras data set by taking the accuracy and the knowledge gain of the learned graphs into account.eng
dc.description.versionpublished
dc.identifier.citationAdvances in intelligent data analysis XI : 11th international symposium ; proceedings; IDA 2012, Helsinki, Finland, October 25 - 27, 2012 / Jaakko Hollmén ... (ed.). - Berlin [u.a.] : Springer, 2012. - S. 264-275. (Lecture notes in computer science ; 7619). - ISBN 978-3-642-34155-7deu
dc.identifier.doi10.1007/978-3-642-34156-4_25deu
dc.identifier.ppn383801702deu
dc.identifier.urihttp://kops.uni-konstanz.de/handle/123456789/23714
dc.language.isoengdeu
dc.legacy.dateIssued2013-06-20deu
dc.rightsterms-of-usedeu
dc.rights.urihttps://rightsstatements.org/page/InC/1.0/deu
dc.subject.ddc004deu
dc.titleLearning Pattern Graphs for Multivariate Temporal Pattern Retrievaleng
dc.typeINPROCEEDINGSdeu
dspace.entity.typePublication
kops.citation.bibtex
@inproceedings{Peter2012Learn-23714,
  year={2012},
  doi={10.1007/978-3-642-34156-4_25},
  title={Learning Pattern Graphs for Multivariate Temporal Pattern Retrieval},
  number={7619},
  isbn={978-3-642-34155-7},
  publisher={Springer Berlin Heidelberg},
  address={Berlin, Heidelberg},
  series={Lecture Notes in Computer Science},
  booktitle={Advances in Intelligent Data Analysis XI},
  pages={264--275},
  editor={Hollmén, Jaakko and Klawonn, Frank and Tucker, Allan},
  author={Peter, Sebastian and Höppner, Frank and Berthold, Michael R.}
}
kops.citation.iso690PETER, Sebastian, Frank HÖPPNER, Michael R. BERTHOLD, 2012. Learning Pattern Graphs for Multivariate Temporal Pattern Retrieval. In: HOLLMÉN, Jaakko, ed., Frank KLAWONN, ed., Allan TUCKER, ed.. Advances in Intelligent Data Analysis XI. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012, pp. 264-275. Lecture Notes in Computer Science. 7619. ISBN 978-3-642-34155-7. Available under: doi: 10.1007/978-3-642-34156-4_25deu
kops.citation.iso690PETER, Sebastian, Frank HÖPPNER, Michael R. BERTHOLD, 2012. Learning Pattern Graphs for Multivariate Temporal Pattern Retrieval. In: HOLLMÉN, Jaakko, ed., Frank KLAWONN, ed., Allan TUCKER, ed.. Advances in Intelligent Data Analysis XI. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012, pp. 264-275. Lecture Notes in Computer Science. 7619. ISBN 978-3-642-34155-7. Available under: doi: 10.1007/978-3-642-34156-4_25eng
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kops.sourcefieldHOLLMÉN, Jaakko, ed., Frank KLAWONN, ed., Allan TUCKER, ed.. <i>Advances in Intelligent Data Analysis XI</i>. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012, pp. 264-275. Lecture Notes in Computer Science. 7619. ISBN 978-3-642-34155-7. Available under: doi: 10.1007/978-3-642-34156-4_25deu
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kops.submitter.emailchristoph.petzmann@uni-konstanz.dedeu
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source.contributor.editorKlawonn, Frank
source.contributor.editorTucker, Allan
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source.relation.ispartofseriesLecture Notes in Computer Science
source.titleAdvances in Intelligent Data Analysis XI

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