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Probabilistic evaluation of process model matching techniques
Kuss, Elena
;
Leopold, Henrik
;
Aa, Han van der
;
Stuckenschmidt, Heiner
;
Reijers, Hajo A.
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DOI:
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https://doi.org/10.1007/978-3-319-46397-1_22
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URL:
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https://madoc.bib.uni-mannheim.de/41112
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Additional URL:
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http://link.springer.com/chapter/10.1007/978-3-319...
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URN:
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urn:nbn:de:bsz:180-madoc-411127
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Document Type:
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Conference or workshop publication
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Year of publication:
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2016
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Book title:
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Conceptual modeling : 35th international conference, ER 2016, Gifu, Japan, November 14-17, 2016 : proceedings
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The title of a journal, publication series:
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Lecture Notes in Computer Science
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Volume:
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9974
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Page range:
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279-292
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Date of the conference:
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November 14-17, 2016
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Publisher:
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Comyn-Wattiau, Isabelle
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Place of publication:
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Berlin [u.a.]
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Publishing house:
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Springer
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ISBN:
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978-3-319-46396-4 , 978-3-319-46397-1
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ISSN:
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0302-9743 , 1611-3349
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Publication language:
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English
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Institution:
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School of Business Informatics and Mathematics > Practical Computer Science II: Artificial Intelligence (Stuckenschmidt 2009-)
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Subject:
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004 Computer science, internet
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Keywords (English):
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Process Model Matching , Non-binary Evaluation , Matching Performance Assessment
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Abstract:
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Process model matching refers to the automatic identification of corresponding activities between two process models. It represents
the basis for many advanced process model analysis techniques such as
the identification of similar process parts or process model search. A
central problem is how to evaluate the performance of process model
matching techniques. Often, not even humans can agree on a set of correct correspondences. Current evaluation methods, however, require a
binary gold standard, which clearly defines which correspondences are
correct. The disadvantage of this evaluation method is that it does not
take the true complexity of the matching problem into account and does
not fairly assess the capabilities of a matching technique. In this paper,
we propose a novel evaluation method for process model matching techniques. In particular, we build on the assessment of multiple annotators
to define probabilistic notions of precision and recall. We use the dataset
and the results of the Process Model Matching Contest 2015 to assess and
compare our evaluation method. We found that our probabilistic evaluation method assigns different ranks to the matching techniques from the
contest and allows to gain more detailed insights into their performance.
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 | Dieser Eintrag ist Teil der Universitätsbibliographie. |
 | Das Dokument wird vom Publikationsserver der Universitätsbibliothek Mannheim bereitgestellt. |
 Search Authors in
BASE:
Kuss, Elena
;
Leopold, Henrik
;
Aa, Han van der
;
Stuckenschmidt, Heiner
;
Reijers, Hajo A.
Google Scholar:
Kuss, Elena
;
Leopold, Henrik
;
Aa, Han van der
;
Stuckenschmidt, Heiner
;
Reijers, Hajo A.
ORCID:
Kuss, Elena ; Leopold, Henrik ; Aa, Han van der  ORCID: 0000-0002-4200-4937 ; Stuckenschmidt, Heiner ORCID: 0000-0002-0209-3859 ; Reijers, Hajo A.
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