Open AccessData‐driven business process similarity
Author(s) -
Amiri Mohammad Javad,
Koupaee Mahnaz
Publication year - 2017
Publication title -
iet software
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.305
H-Index - 43
eISSN - 1751-8814
pISSN - 1751-8806
DOI - 10.1049/iet-sen.2016.0256
Subject(s) - similarity (geometry) , business process , process (computing) , computer science , business process management , data mining , business process modeling , business process discovery , process mining , artifact centric business process model , process modeling , process management , work in process , artificial intelligence , engineering , operations management , image (mathematics) , operating system
Although measuring the similarity of business processes based on activity labels, structural and behavioural factors can be effective, defining inexact and incomplete labels and the existence of multiple labels for similar activities cause challenges for determining similar processes. Recent attempts to consider data in business process management and the support of data modelling in business process standards have led to the creation of multiple business models with data access. In this study, a method considering data for measuring business process similarity is presented in which first the similarity of activities is measured according to their structures and behaviours in a process and also their data access. Then based on the similarity of activities, the similarity of processes is determined using the proposed algorithm.