The Community for Technology Leaders
RSS Icon
Issue No.05 - Sept.-Oct. (2013 vol.17)
pp: 10-20
Claudio Di Ciccio , Sapienza University of Rome
Massimo Mecella , Sapienza University of Rome
MailOfMine aims at automatically building a set of workflow models--which represent the artful processes behind knowledge workers' activities--on top of a collection of email messages. Such models formalize the unspecified agile processes that knowledge workers autonomously perform: because these models aren't defined a priori by experts but are rather inferred from real-life scenarios, they're guaranteed to respect true workflow executions. Moreover, knowledge workers can share, compare, and preserve such models to put in evidence their best practices and thus benefit the entire business. Finally, workers and organizations can analyze such processes to determine bottlenecks and delays in actual executions. MailOfMine describes workflow models according to a declarative approach, with a specific visual notation.
Electronic mail, Speech processing, Data mining, Internet, Knowledge management, Workflow management software, Collaborative work,electronic mail, process mining, declarative workflow models, workflow management, mining methods and algorithms, text mining
Claudio Di Ciccio, Massimo Mecella, "Mining Artful Processes from Knowledge Workers' Emails", IEEE Internet Computing, vol.17, no. 5, pp. 10-20, Sept.-Oct. 2013, doi:10.1109/MIC.2013.60
1. P. Warren et al., “Improving Knowledge Worker Productivity — the Active Integrated Approach,” BT Technology J., vol. 26, no. 2, 2009, pp. 165-176.
2. C. Di Ciccio and M. Mecella, “A Two-Step Fast Algorithm for the Automated Discovery of Declarative Workflows,” IEEE Symp. Computational Intelligence and Data Mining, IEEE, 2013.
3. C. Di Ciccio, T. Catarci, and M. Mecella, “Representing and Visualizing Mined Artful Processes in MailOfMine,” Proc. 7th Conf. Workgroup Human-Computer Interaction and Usability Eng. of the Austrian Computer Society (USAB 11), LNCS 7058, Springer, 2011, pp. 83-94.
4. V.R. de Carvalho and W.W. Cohen, “Learning to Extract Signature and Reply Lines from Email,” Proc. 1st Conf. Email and Anti-Spam, 2004;
5. J. Searle, A Taxonomy of Illocutionary Acts, Univ. Minnesota Press, 1975.
6. W.W. Cohen, V.R. Carvalho, and T.M. Mitchell, “Learning to Classify Email into ‘Speech Acts,’” Proc. Conf. Empirical Methods in Natural Language Processing, ACL, 2004, pp. 309-316.
7. F.M. Maggi, A.J. Mooij, and W.M.P. van der Aalst, “User-Guided Discovery of Declarative Process Models,” Proc. 2011 IEEE Symp. Computational Intelligence and Data Mining (CIDM 11), IEEE, 2011, pp. 192-199.
8. M. Pesic, H. Schonenberg, and W.M.P. van der Aalst, “Declare: Full Support for Loosely Structured Processes,” Proc. 11th IEEE Int'l Enterprise Distributed Object Computing Conf. (EDOC 07), IEEE CS, 2007, pp. 287-300.
84 ms
(Ver 2.0)

Marketing Automation Platform Marketing Automation Tool