eprintid: 3159
rev_number: 7
eprint_status: archive
userid: 307
dir: disk0/00/00/31/59
datestamp: 2018-11-14 04:32:25
lastmod: 2018-11-14 04:32:25
status_changed: 2018-11-14 04:32:25
type: book_section
metadata_visibility: show
creators_name: Bui, Hong Nhung
creators_name: Nguyen, Tri Thanh
creators_name: Nguyen, Thi Cham
creators_name: Ha, Quang Thuy
creators_id: nhungbth@hvnh.edu.vn
creators_id: ntthanh@vnu.edu.vn
creators_id: nthicham@hpmu.edu.vn
creators_id: thuyhq@vnu.edu.vn
title: A New Trace Clustering Algorithm Based on Context in Process Mining
ispublished: pub
subjects: IT
abstract: 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.
date: 2018-08
date_type: published
publisher: Springer
official_url: https://link.springer.com/chapter/10.1007%2F978-3-319-99368-3_50
full_text_status: public
series: Lecture Notes in Computer Science
number: 11103
pagerange: 644-657
pages: 50
refereed: FALSE
isbn: ISBN 978-3-319-76080-3
book_title: International Joint Conference on Rough Sets (IJCRS 2018)
editors_name: Nguyen, Hung Son
editors_name: Ha, Quang Thuy
editors_name: li, Tianrui
editors_name: Małgorzata, Przybyła-Kasperek
editors_id: thuyhq@vnu.edu.vn
citation:   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     
document_url: https://eprints.uet.vnu.edu.vn/eprints/id/eprint/3159/1/18_02__Book_RoughSets.pdf