Presentations 2016

Decomposed Replay Using Hiding and Reduction
Presented at the PNSE 2016 workshop on Tuesday June 21. Presentation of the following publication:
  • [PDF] H. M. W. Verbeek, “Decomposed replay using hiding and reduction,” in PNSE 2016 workshop proceedings, Torun, Poland, 2016.
    [Bibtex]
    @InProceedings{Verbeek16a,
    Title = {Decomposed Replay using Hiding and Reduction},
    Author = {Verbeek, H. M. W.},
    Booktitle = {{PNSE} 2016 Workshop Proceedings},
    Year = {2016},
    Address = {Torun, Poland},
    Editor = {Cabac, L. and Kristensen, L. and R\"{o}lke, H.},
    Month = {June},
    Note = {Accepted for publication},
    Abstract = {In the area of process mining, decomposed replay has been proposed to be able to deal with nets and logs containing many different activities. The main assumption behind this decomposition is that replaying many subnets and sublogs containing only some activities is faster then replaying a single net and log containing many activities. Although for many nets and logs this assumption does hold, there are also nets and logs for which it does not hold. This paper shows an example net and log for which the decomposed replay may take way more time, and provides an explanation why this is the case. Next, to mitigate this problem, this paper proposes an alternative decomposed replay, and shows that this alternative decomposed replay is faster than the monolithic replay even for the problematic cases as identified earlier.owever, the alternative decomposed replay is often slower than the original decomposed approach. An advantage of the alternative decomposed approach over the original approach is that its cost estimates are typically better.},
    Url = {http://www.win.tue.nl/~hverbeek/wp-content/papercite-data/pdf/verbeek16a.pdf}
    }
Merging Alignments for Decomposed Replay
Presented at the Petri Nets 2016 conference on Thursday June 23. Presentation of the following publication:
  • [PDF] [DOI] H. M. W. Verbeek and W. M. P. v. d. Aalst, “Merging alignments for decomposed replay,” in Application and theory of Petri nets and concurrency, Torun, Poland, 2016, pp. 219-239.
    [Bibtex]
    @InProceedings{Verbeek16,
    Title = {Merging Alignments for Decomposed Replay},
    Author = {Verbeek, H. M. W and Aalst, W. M. P. v. d.},
    Booktitle = {Application and Theory of {P}etri Nets and Concurrency},
    Year = {2016},
    Address = {Torun, Poland},
    Editor = {Kordon, F and Moldt, D.},
    Month = {June},
    Pages = {219--239},
    Publisher = {Springer International Publishing},
    Series = {LNCS},
    Volume = {9698},
    Abstract = {In the area of process mining, conformance checking aims to find an optimal alignment between an event log (which captures the activities that actually have happened) and a Petri net (which describes expected or normative behavior). Optimal alignments highlight discrepancies between observed and modeled behavior. To find an optimal alignment, a potentially challenging optimization problem needs to be solved based on a predefined cost function for misalignments. Unfortunately, this may be very time consuming for larger logs and models and often intractable. A solution is to decompose the problem of finding an optimal alignment in many smaller problems that are easier to solve. Decomposition can be used to detect conformance problems in less time and provides a lower bound for the costs of an optimal alignment. Although the existing approach is able to decide whether a trace fits or not, it does not provide an overall alignment. In this paper, we provide an algorithm that is able provide such an optimal alignment from the decomposed alignments if this is possible. Otherwise, the algorithm produces a so-called pseudo-alignment that can still be used to pinpoint non-conforming parts of log and model. The approach has been implemented in ProM and tested on various real-life event logs.},
    Doi = {10.1007/978-3-319-39086-4_14},
    Url = {http://www.win.tue.nl/~hverbeek/wp-content/papercite-data/pdf/verbeek16.pdf}
    }

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