relation: https://eprints.uet.vnu.edu.vn/eprints/id/eprint/3159/
title: A New Trace Clustering Algorithm Based on Context in Process Mining
creator: Bui, Hong Nhung
creator: Nguyen, Tri Thanh
creator: Nguyen, Thi Cham
creator: Ha, Quang Thuy
subject: Information Technology (IT)
description: In process mining, trace clustering is an important technique that at-tracts the attention of researchers to solve the large and complex volume of event logs. Traditional trace clustering often uses available data mining algorithms which do not exploit the characteristic of processes. In this study, we propose a new trace clustering algorithm, especially for the process mining, based on the using trace context. The proposed clustering algorithm can automatic detects the number of clusters, and it does not need a convergence iteration like traditional ones like K-means. The algorithm takes two loops over the input to generate the clusters, thus the complexity is greatly reduced. Experimental results show that our method also has good results when compared to traditional methods.
publisher: Springer
contributor: Nguyen, Hung Son
contributor: Ha, Quang Thuy
contributor: li, Tianrui
contributor: Małgorzata, Przybyła-Kasperek
date: 2018-08
type: Book Section
type: NonPeerReviewed
format: application/pdf
language: en
identifier: https://eprints.uet.vnu.edu.vn/eprints/id/eprint/3159/1/18_02__Book_RoughSets.pdf
identifier:   Bui, Hong Nhung and Nguyen, Tri Thanh and Nguyen, Thi Cham and Ha, Quang Thuy  (2018) A New Trace Clustering Algorithm Based on Context in Process Mining.   In:  International Joint Conference on Rough Sets (IJCRS 2018).   Lecture Notes in Computer Science  (11103).  Springer, pp. 644-657.  ISBN ISBN 978-3-319-76080-3     
relation: https://link.springer.com/chapter/10.1007%2F978-3-319-99368-3_50