eprintid: 3160
rev_number: 9
eprint_status: archive
userid: 307
dir: disk0/00/00/31/60
datestamp: 2018-11-14 04:32:58
lastmod: 2018-11-14 04:32:58
status_changed: 2018-11-14 04:32:58
type: article
metadata_visibility: show
creators_name: Bui, Hong Nhung
creators_name: Ha, Quang Thuy
creators_name: Nguyen, Tri Thanh
creators_id: nhungbth@hvnh.edu.vn
creators_id: thuyhq@vnu.edu.vn
creators_id: ntthanh@vnu.edu.vn
title: A novel similarity measure for trace clustering based on normalized google distance.
ispublished: pub
subjects: IT
subjects: Scopus
divisions: fac_fit
abstract: In trace clustering, a problem of process mining, traditional distance measures only focus on the local relationship between trace pairs. In this paper, we propose a new method to measure the global relationship of the traces based on the Normalized Google Distance. Experimental results show that our method not only outperforms alternatives but also helps to speed up the trace clustering.
date: 2018-08
date_type: published
publisher: The Pushpa Publishing House
official_url: http://www.pphmj.com/abstract/11903.htm
full_text_status: public
publication: JP Journal of Heat and Mass Transfer
volume: Specia
number: 3
pagerange: 341-346
refereed: FALSE
issn: ISSN: 0973-5763
related_url_url: http://www.pphmj.com/abstract/11903.htm
citation:   Bui, Hong Nhung and Ha, Quang Thuy and Nguyen, Tri Thanh  (2018) A novel similarity measure for trace clustering based on normalized google distance.  JP Journal of Heat and Mass Transfer, Specia  (3).   pp. 341-346.  ISSN ISSN: 0973-5763     
document_url: https://eprints.uet.vnu.edu.vn/eprints/id/eprint/3160/1/18_9_An%20novel%20similarity%20measure%20for%20trace%20clustering%20based%20on%20Normalized%20Google%20Distance.pdf