@inproceedings{3bbedc8daf6d44e69391cfd5039fd5ab,
title = "Discovering behavioural patterns in knowledge-intensive collaborative processes",
abstract = "Domains like emergency management, health care, or research and innovation development, are characterized by the execution of so-called knowledge-intensive processes. Such processes are typically highly uncertain, with little or no structure; consequently, classical process discovery techniques, aimed at extracting complete process schemas from execution logs, usually provide a limited support in analysing these processes. As a remedy, in the present work we propose a methodology aimed at extracting relevant subprocesses, representing meaningful collaboration behavioural patterns. We consider a real case study regarding the development of research activities, to test the approach and compare its results with the outcome of classical process discovery techniques.",
author = "Claudia Diamantini and Laura Genga and Domenico Potena and Emanuele Storti",
year = "2014",
doi = "10.1007/978-3-319-17876-9_10",
language = "English",
isbn = "978-3-319-17875-2",
series = "Lecture Notes in Computer Science",
publisher = "Springer",
pages = "149--163",
editor = "Annalisa Appice and Michelangelo Ceci and Corrado Loglisci and Giuseppe Manco and Elio Masciari and Ras, {Zbigniew W.}",
booktitle = "New Frontiers in Mining Complex Patterns",
address = "Germany",
note = "New frontiers in Mining Complex Patterns 2014, NFMCP 2014 ; Conference date: 19-09-2014 Through 19-09-2014",
}