eprintid: 2817
rev_number: 6
eprint_status: archive
userid: 286
dir: disk0/00/00/28/17
datestamp: 2017-12-20 02:59:45
lastmod: 2017-12-20 02:59:45
status_changed: 2017-12-20 02:59:45
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
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: 2017
date_type: published
full_text_status: none
publication: Journal of Electronics and Communications
refereed: FALSE
issn: 0973-7006
citation:   Bui, Hong Nhung and Ha, Quang Thuy and Nguyen, Tri Thanh  (2017) A novel similarity measure for trace clustering based on normalized google distance.  Journal of Electronics and Communications .    ISSN 0973-7006