TY - GEN
T1 - Mining and querying process change information based on change trees
AU - Kaes, Georg
AU - Rinderle-Ma, Stefanie
N1 - Publisher Copyright:
© Springer-Verlag Berlin Heidelberg 2015.
PY - 2015
Y1 - 2015
N2 - Analyzing process change logs provides valuable information about the evolution of process instances. This information can be used to support responsible users in planning and executing future changes. Change mining results in a change process, which represents the dependencies between process changes mined from the change log. However, when it comes to highly adaptive process settings, multiple limitations of the change process representation can be found, i.e., based on change processes it is not possible to provide answers to important analysis questions such as ‘How many instances have evolved in a similar way?’ or ‘Which changes have occurred following a particular change?’. In this paper, change trees and n-gram change trees are introduced to serve as a basis to analyze changes in highly adaptive process instances. Moreover, algorithms for discovering change trees and n-gram change trees from change logs are presented. The applicability of the approach is evaluated based on a systematic comparison with change mining, a proof-of-concept implementation and by analyzing real-world data.
AB - Analyzing process change logs provides valuable information about the evolution of process instances. This information can be used to support responsible users in planning and executing future changes. Change mining results in a change process, which represents the dependencies between process changes mined from the change log. However, when it comes to highly adaptive process settings, multiple limitations of the change process representation can be found, i.e., based on change processes it is not possible to provide answers to important analysis questions such as ‘How many instances have evolved in a similar way?’ or ‘Which changes have occurred following a particular change?’. In this paper, change trees and n-gram change trees are introduced to serve as a basis to analyze changes in highly adaptive process instances. Moreover, algorithms for discovering change trees and n-gram change trees from change logs are presented. The applicability of the approach is evaluated based on a systematic comparison with change mining, a proof-of-concept implementation and by analyzing real-world data.
UR - http://www.scopus.com/inward/record.url?scp=84952332650&partnerID=8YFLogxK
U2 - 10.1007/978-3-662-48616-0_17
DO - 10.1007/978-3-662-48616-0_17
M3 - Conference contribution
AN - SCOPUS:84952332650
SN - 9783662486153
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 269
EP - 284
BT - Service-Oriented Computing - 13th International Conference, ICSOC 2015, Proceedings
A2 - Barros, Alistair
A2 - Dam, Hoa Khanh
A2 - Grigori, Daniela
A2 - Narendra, Nanjangud C.
PB - Springer Verlag
T2 - 13th International Conference on Service-Oriented Computing, CSOC 2015
Y2 - 16 November 2015 through 19 November 2015
ER -