eprintid: 2889
rev_number: 20
eprint_status: archive
userid: 307
dir: disk0/00/00/28/89
datestamp: 2017-12-29 08:48:12
lastmod: 2018-01-04 14:28:10
status_changed: 2017-12-29 08:50:56
type: conference_item
metadata_visibility: show
creators_name: Nguyen, Van Tham
creators_name: Tran, Trong Hieu
creators_id: thamnv.nute@gmail.com
creators_id: hieutt@vnu.edu.vn
title: Inconsistency measures for probabilistic knowledge bases
ispublished: pub
subjects: IT
divisions: fac_fit
abstract: One of the major concerns in knowledge integration is inconsistencies in knowledge bases. An inconsistency measure is  a  tool  that  helps  analyzing  inconsistency  knowledge  bases and  resolving  inconsistencies.  In  recent  years,  a  wide  range  of measures with desirable properties have been proposed, however, these  measures  often  correspond  to  logical,  or  probabilistic-logical  framework.  In  this  paper,  we  investigate  several  inconsistency  measures  and  their  properties  for  the  knowledge  bases represented  by  probabilistic framework.
date: 2017
date_type: published
publisher: IEEE
full_text_status: public
pres_type: paper
publication: 9th International Conference on Knowledge and Systems Engineering (KSE) 2017
event_title: The 2017 International Conference on Knowledge and Systems Engineering (KSE)
event_location: Hue, Vietnam
event_dates: 19-21 October 2017
event_type: conference
refereed: TRUE
citation:   Nguyen, Van Tham and Tran, Trong Hieu  (2017) Inconsistency measures for probabilistic knowledge bases.  In: The 2017 International Conference on Knowledge and Systems Engineering (KSE), 19-21 October 2017, Hue, Vietnam.     
document_url: https://eprints.uet.vnu.edu.vn/eprints/id/eprint/2889/2/KSE_2017.pdf