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  • 标题:Evaluation of Temporal Datasets via Interval Temporal Logic Model Checking
  • 本地全文:下载
  • 作者:Dario Della Monica ; David de Frutos-Escrig ; Angelo Montanari
  • 期刊名称:LIPIcs : Leibniz International Proceedings in Informatics
  • 电子版ISSN:1868-8969
  • 出版年度:2017
  • 卷号:90
  • 页码:11:1-11:18
  • DOI:10.4230/LIPIcs.TIME.2017.11
  • 出版社:Schloss Dagstuhl -- Leibniz-Zentrum fuer Informatik
  • 摘要:The problem of temporal dataset evaluation consists in establishing to what extent a set of temporal data (histories) complies with a given temporal condition. It presents a strong resemblance with the problem of model checking enhanced with the ability of rating the compliance degree of a model against a formula. In this paper, we solve the temporal dataset evaluation problem by suitably combining the outcomes of model checking an interval temporal logic formula against sets of histories (finite interval models), possibly taking into account domain-dependent measures/criteria, like, for instance, sensitivity, specificity, and accuracy. From a technical point of view, the main contribution of the paper is a (deterministic) polynomial time algorithm for interval temporal logic model checking over finite interval models. To the best of our knowledge, this is the first application of a (truly) interval temporal logic model checking in the area of temporal databases and data mining rather than in the formal verification setting.
  • 关键词:Dataset Evaluation; Temporal Databases; Model Checking; Interval Temporal Logics
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