@inproceedings{SchmidtM{\"o}hringZimmermannetal.2016,
  author    = {Schmidt, Rainer and M{\"o}hring, Michael and Zimmermann, Alfred and H{\"a}rting, Ralf-Christian and Keller, Barbara},
  title     = {Potentials of Image Mining for business process management},
  booktitle = {Intelligent decision technologies 2016 : proceedings of the 8th KES International Conference on Intelligent Decision Technologies (KES-IDT 2016). - Part II},
  editor    = {Czarnowski, Ireneusz},
  isbn      = {978-3-319-39627-9},
  doi       = {10.1007/978-3-319-39627-9_38},
  institution = {Informatik},
  pages     = {429 -- 440},
  year      = {2016},
  abstract  = {An enormous amount of data in the context of business processes is stored as images. They contain valuable information for business process management. Up to now this data had to be integrated manually into the business process. By advances of capturing it is possible to extract information from an increasing number of images. Therefore, we systematically investigate the potentials of Image Mining for business process management by a literature research and an in-depth analysis of the business process lifecycle. As a first step to evaluate our research, we developed a prototype for recovering process model information from drawings using Rapidminer.},
  language  = {en}
}