Sign inSign up
Calculating distance measure for clustering in multi-relational settings thumbnail
Pause
Mute
Subtitles
Playback speed
0.25
0.5
0.75
1
1.25
1.5
1.75
2
Full screen

Calculating distance measure for clustering in multi-relational settings

Published on Oct 30, 20131776 Views

Olegas Niaksu

The paper deals with a distance based multi-relational clustering application in a real data case study. A novel method for a dissimilarity matrix calculation in multi-relational settings has been pro

SiKDD 2013 - Ljubljana

Related categories

Artificial IntelligenceData Mining

Chapter list

Calculating distance measure for MRDM clustering00:00
Setting the scene - data mining in healthcare - 201:21
Setting the scene - data mining in healthcare - 101:25
EHR adoption in the USA01:59
Trend lines of DM applications in medicine related publications02:51
Survey on data mining application03:43
Motivation04:22
PubMed database and MESH06:29
Intro to MESH concepts06:51
Multi-relational data mining07:38
Clustering in multi-relational settings10:17
E-R diagram12:58
MRDM clustering approach - informally13:30
Distance measure for MRDM clustering14:06
Gower general coefficient of similarity14:34
Ochiai-Barkman coefficient16:14
Weights calculation17:23
Case study18:03
Case study realization18:27
Case study outcomes - 120:24
Case study outcomes - 222:18
Discussion23:24
Thank you for your attention!23:34