License: Creative Commons Attribution 3.0 Unported license (CC BY 3.0)
When quoting this document, please refer to the following
DOI: 10.4230/LIPIcs.TIME.2020.11
URN: urn:nbn:de:0030-drops-129792
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2020/12979/
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Sciavicco, Guido ; Zavatteri, Matteo ; Villa, Tiziano

Mining Significant Temporal Networks Is Polynomial

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LIPIcs-TIME-2020-11.pdf (0.5 MB)

Abstract

A Conditional Simple Temporal Network with Uncertainty and Decisions (CSTNUD) is a formalism that tackles controllable and uncontrollable durations as well as controllable and uncontrollable choices simultaneously. In the classic top-down model-based engineering approach, a designer builds a CSTNUD to model, validate and execute some temporal plan of interest. Instead, in this paper, we investigate the bottom-up approach by providing a deterministic polynomial time algorithm to mine a CSTNUD from a set of execution traces (i.e., a log). This paper paves the way for the design of controllable temporal networks mined from traces that also contain information on uncontrollable events.

BibTeX - Entry

@InProceedings{sciavicco_et_al:LIPIcs:2020:12979,
  author =	{Guido Sciavicco and Matteo Zavatteri and Tiziano Villa},
  title =	{{Mining Significant Temporal Networks Is Polynomial}},
  booktitle =	{27th International Symposium on Temporal Representation and Reasoning (TIME 2020)},
  pages =	{11:1--11:12},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-167-2},
  ISSN =	{1868-8969},
  year =	{2020},
  volume =	{178},
  editor =	{Emilio Mu{\~n}oz-Velasco and Ana Ozaki and Martin Theobald},
  publisher =	{Schloss Dagstuhl--Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/opus/volltexte/2020/12979},
  URN =		{urn:nbn:de:0030-drops-129792},
  doi =		{10.4230/LIPIcs.TIME.2020.11},
  annote =	{Keywords: Mining temporal constraints, cstnud, uncertainty, significant temporal network}
}

Keywords: Mining temporal constraints, cstnud, uncertainty, significant temporal network
Collection: 27th International Symposium on Temporal Representation and Reasoning (TIME 2020)
Issue Date: 2020
Date of publication: 15.09.2020

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