@article{BaierDiCiccioMendlingetal.2018,
  author    = {Baier, Thomas and Di Ciccio, Claudio and Mendling, Jan and Weske, Mathias},
  title     = {Matching events and activities by integrating behavioral aspects and label analysis},
  series = {Software and systems modeling},
  volume    = {17},
  journal   = {Software and systems modeling},
  number    = {2},
  publisher = {Springer},
  address   = {Heidelberg},
  issn      = {1619-1366},
  doi       = {10.1007/s10270-017-0603-z},
  pages     = {573 -- 598},
  year      = {2018},
  abstract  = {Nowadays, business processes are increasingly supported by IT services that produce massive amounts of event data during the execution of a process. These event data can be used to analyze the process using process mining techniques to discover the real process, measure conformance to a given process model, or to enhance existing models with performance information. Mapping the produced events to activities of a given process model is essential for conformance checking, annotation and understanding of process mining results. In order to accomplish this mapping with low manual effort, we developed a semi-automatic approach that maps events to activities using insights from behavioral analysis and label analysis. The approach extracts Declare constraints from both the log and the model to build matching constraints to efficiently reduce the number of possible mappings. These mappings are further reduced using techniques from natural language processing, which allow for a matching based on labels and external knowledge sources. The evaluation with synthetic and real-life data demonstrates the effectiveness of the approach and its robustness toward non-conforming execution logs.},
  language  = {en}
}
@misc{HanvanderDiCiccioLeopoldetal.2019,
  author    = {Han van der, Aa and Di Ciccio, Claudio and Leopold, Henrik and Reijers, Hajo A.},
  title     = {Extracting Declarative Process Models from Natural Language},
  series = {Advanced Information Systems Engineering (CAISE 2019)},
  volume    = {11483},
  journal   = {Advanced Information Systems Engineering (CAISE 2019)},
  publisher = {Springer},
  address   = {Cham},
  isbn      = {978-3-030-21290-2},
  issn      = {0302-9743},
  doi       = {10.1007/978-3-030-21290-2_23},
  pages     = {365 -- 382},
  year      = {2019},
  abstract  = {Process models are an important means to capture information on organizational operations and often represent the starting point for process analysis and improvement. Since the manual elicitation and creation of process models is a time-intensive endeavor, a variety of techniques have been developed that automatically derive process models from textual process descriptions. However, these techniques, so far, only focus on the extraction of traditional, imperative process models. The extraction of declarative process models, which allow to effectively capture complex process behavior in a compact fashion, has not been addressed. In this paper we close this gap by presenting the first automated approach for the extraction of declarative process models from natural language. To achieve this, we developed tailored Natural Language Processing techniques that identify activities and their inter-relations from textual constraint descriptions. A quantitative evaluation shows that our approach is able to generate constraints that closely resemble those established by humans. Therefore, our approach provides automated support for an otherwise tedious and complex manual endeavor.},
  language  = {en}
}
@article{MendlingWebervanderAalstetal.2018,
  author    = {Mendling, Jan and Weber, Ingo and van der Aalst, Wil and Brocke, Jan Vom and Cabanillas, Cristina and Daniel, Florian and Debois, Soren and Di Ciccio, Claudio and Dumas, Marlon and Dustdar, Schahram and Gal, Avigdor and Garcia-Banuelos, Luciano and Governatori, Guido and Hull, Richard and La Rosa, Marcello and Leopold, Henrik and Leymann, Frank and Recker, Jan and Reichert, Manfred and Reijers, Hajo A. and Rinderle-Ma, Stefanie and Solti, Andreas and Rosemann, Michael and Schulte, Stefan and Singh, Munindar P. and Slaats, Tijs and Staples, Mark and Weber, Barbara and Weidlich, Matthias and Weske, Mathias and Xu, Xiwei and Zhu, Liming},
  title     = {Blockchains for Business Process Management},
  series = {ACM Transactions on Management Information Systems},
  volume    = {9},
  journal   = {ACM Transactions on Management Information Systems},
  number    = {1},
  publisher = {Association for Computing Machinery},
  address   = {New York},
  issn      = {2158-656X},
  doi       = {10.1145/3183367},
  pages     = {1 -- 16},
  year      = {2018},
  abstract  = {Blockchain technology offers a sizable promise to rethink the way interorganizational business processes are managed because of its potential to realize execution without a central party serving as a single point of trust (and failure). To stimulate research on this promise and the limits thereof, in this article, we outline the challenges and opportunities of blockchain for business process management (BPM). We first reflect how blockchains could be used in the context of the established BPM lifecycle and second how they might become relevant beyond. We conclude our discourse with a summary of seven research directions for investigating the application of blockchain technology in the context of BPM.},
  language  = {en}
}