Annotating and Mining for Effects of Processes

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dc.contributor.authorRoy, Suman
dc.contributor.authorSantiputri, Metta
dc.contributor.authorGhose, Aditya
dc.date.accessioned2023-06-28T05:35:43Z
dc.date.available2023-06-28T05:35:43Z
dc.date.issued2016-10-07
dc.description.abstrakWe provide a novel explicit annotation of a process model by way of accumulating effects of individual tasks specified by analysts using belief bases and computing the accumulated effect up to the point of execution of the process model in an automated manner. This tech- nique permits the analyst to specify immediate effect annotations in a practitioner-accessible simple propositional logic formulas and generates a sequence of tasks along with cumulative effects, called effect logs. Fur- ther we propose and solve an effect mining problem, that is, given an effect log discover the process model with effect annotations of individ- ual tasks which is close to the original annotated process model.en_US
dc.identifier.citationRoy, S., Santiputri, M., Ghose, A. (2016). Annotating and Mining for Effects of Processes. In: Comyn-Wattiau, I., Tanaka, K., Song, IY., Yamamoto, S., Saeki, M. (eds) Conceptual Modeling. ER 2016. Lecture Notes in Computer Science(), vol 9974. Springer, Cham. https://doi.org/10.1007/978-3-319-46397-1_24en_US
dc.identifier.isbn978-3-319-46397-1
dc.identifier.issn0302-9743
dc.identifier.other10.1007/978-3-319-46397-1
dc.identifier.urihttps://repository.polibatam.ac.id/xmlui/handle/123456789/1718
dc.language.isoenen_US
dc.publisherSpringeren_US
dc.relation.ispartofseriesLecture Notes in Computer Science;volume 9974
dc.relation.ispartofseriesProceedings of the.35th International Conference (ER 2016);
dc.subjectBusiness process modelingen_US
dc.subjectSemantic annotationen_US
dc.subjectEffectsen_US
dc.subjectBelief basesen_US
dc.subjectAnnotated processesen_US
dc.subjectEffect logsen_US
dc.subjectEffect miningen_US
dc.titleAnnotating and Mining for Effects of Processesen_US
dc.typeBook chapteren_US
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