A clustering algorithm based on minimum spanning tree with E-learning applications

Siyang Wang, Zeping Tang, Yanghui Rao, Haoran Xie, Fu Lee Wang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Citations (Scopus)

Abstract

The rapid development of web-based learning applications has generated large amounts of learning resources. Faced with this situation, clustering is valuable to group modeling and intelligent tutoring. In traditional clustering algorithms, the initial centroid of each cluster is often assigned randomly. Sometimes it is very difficult to get an effective clustering result. In this paper, we propose a new clustering algorithm based on a minimum spanning tree, which includes the elimination and construction processes. In the elimination phase, the Euclidean distance is used to measure the density. Objects with low densities are considered as noise and eliminated. In the construction phase, a minimum spanning tree is constructed to choose the initial centroid based on the degree of freedom. Extensive evaluations using datasets with different properties validate the effectiveness of the proposed clustering algorithm. Furthermore, we study how to employ the clustering algorithms in three different e-learning applications.

Original languageEnglish
Title of host publicationCurrent Developments in Web Based Learning - ICWL 2015 International Workshops, KMEL, IWUM, LA, Revised Selected Papers
EditorsDi Zou, Zhiguo Gong, Dickson K.W. Chiu
Pages3-12
Number of pages10
DOIs
Publication statusPublished - 2016
Externally publishedYes
EventInternational Conference on Web Based Learning, ICWL 2015 - Guangzhou, China
Duration: 5 Nov 20158 Nov 2015

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9584 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

ConferenceInternational Conference on Web Based Learning, ICWL 2015
Country/TerritoryChina
CityGuangzhou
Period5/11/158/11/15

Keywords

  • Clustering
  • Density
  • E-learning
  • Minimum spanning tree

Fingerprint

Dive into the research topics of 'A clustering algorithm based on minimum spanning tree with E-learning applications'. Together they form a unique fingerprint.

Cite this