Paper Info
Title
Discovering Business Rules in Knowledge-Intensive Processes Through Decision Mining: An Experimental Study.
Abstract
Decision mining allows discovering rules that constraint the paths that the instances of a business process may follow during its execution. In Knowledge- intensive Processes (KiP), the discovery of such rules is a great challenge because they lack structure. In this context, this experimental study applies a decision mining technique in an event log of a real company that provides ICT infrastructure services. The log comprises structured data (ticket events) and non-structured data (messages exchanged among team members). The goal was to discover tacit decisions that could be potentially declared as business rules for the company. In addition to mining the decision points, we validated the discovered rule with the company w.r.t. their meaning.
Year
DOI
Venue
2017
10.1007/978-3-319-74030-0_44
Lecture Notes in Business Information Processing
Keywords
Field
DocType
Decision mining,Business rules,Knowledge-intensive Processes
Business process,Computer science,Ticket,Information and Communications Technology,Data model,Business rule,Process management
Conference
Volume
ISSN
Citations 
308
1865-1348
2
PageRank 
References 
Authors
0.37
5
4
Name
Order
Citations
PageRank
Júlio Campos120.37
Pedro H. Piccoli Richetti2102.26
Fernanda Araujo Baião317632.72
Flávia Maria Santoro431247.15