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Business Process Instances Discovery from Email Logs

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Date
2017
Notes
25–30 June 2017Honolulu, Hawaii, USA
Dewey
Informatique générale
Sujet
Email analysis; Word2vec; process instance discovery; process mining; process analysis
DOI
http://dx.doi.org/10.1109/SCC.2017.12
Conference date
2017
Book title
2017 IEEE International Conference on Services Computing (SCC)
Publisher
IEEE - Institute of Electrical and Electronics Engineers
Publisher city
Piscataway, NJ
ISBN
978-1-5386-2004-5
URI
https://basepub.dauphine.fr/handle/123456789/19343
Collections
  • LAMSADE : Publications
Metadata
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Author
Jlailaty, Diana
Grigori, Daniela
Belhajjame, Khalid
Type
Communication / Conférence
Item number of pages
19-26
Abstract (EN)
Email is a reliable, confidential, fast, free and easily accessible form of communication. Due to its wide use in personal, but most importantly, professional contexts, email represents a valuable source of information that can be harvested for understanding, reengineering and repurposing undocumented business processes of companies and institutions. Few researchers have investigated the problem of extracting and analyzing the process-oriented information contained in emails. In this paper, we go forward in this direction by proposing a new method to discover business process instances from email logs that uses unsupervised classification techniques. The approach is composed of two clustering steps. The first one uses a powerful semantic similarity measurement method, Word2vec, while the second one uses a similarity measure combing several email attributes. Experimental results are detailed to illustrate and prove our approach contributions.

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