A density-based clustering algorithm with educational applications

Zitong Wang; Peng Kang; Zewei Wu; Yanghui Rao; Fu Lee Wang

doi:10.1007/978-3-319-32865-2_13

A density-based clustering algorithm with educational applications

Zitong Wang, Peng Kang, Zewei Wu, Yanghui Rao, Fu Lee Wang

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

2 Citations (Scopus)

Abstract

With the rapid development of Web 2.0 and interactive technologies, learning resources are proliferating online. Confronting such large volume of educational data, users require effective and efficient methodologies to organize and manage them, which reveals the importance of clustering. In this paper, we first propose a method to estimate the data density, and then apply it to merge learning resources. The proposed algorithm estimates the confidence of any two learning resources to be a pair of neighbors, and conducts clustering by combining the above confidence with the similarities among resources. Experiments are designed to evaluate the performance of our algorithm using the standard clustering datasets. We also demonstrate how to employ the proposed algorithm in educational applications, including e-learner grouping, resource recommendation and usage patterns discovery.

Original language	English
Title of host publication	Current Developments in Web Based Learning - ICWL 2015 International Workshops, KMEL, IWUM, LA, Revised Selected Papers
Editors	Di Zou, Zhiguo Gong, Dickson K.W. Chiu
Pages	118-127
Number of pages	10
DOIs	https://doi.org/10.1007/978-3-319-32865-2_13
Publication status	Published - 2016
Externally published	Yes
Event	International Conference on Web Based Learning, ICWL 2015 - Guangzhou, China Duration: 5 Nov 2015 → 8 Nov 2015

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	9584 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	International Conference on Web Based Learning, ICWL 2015
Country/Territory	China
City	Guangzhou
Period	5/11/15 → 8/11/15

Keywords

Clustering analysis
Data density
E-learning
User modeling

Access to Document

10.1007/978-3-319-32865-2_13

Cite this

Wang, Z., Kang, P., Wu, Z., Rao, Y., & Wang, F. L. (2016). A density-based clustering algorithm with educational applications. In D. Zou, Z. Gong, & D. K. W. Chiu (Eds.), Current Developments in Web Based Learning - ICWL 2015 International Workshops, KMEL, IWUM, LA, Revised Selected Papers (pp. 118-127). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9584 LNCS). https://doi.org/10.1007/978-3-319-32865-2_13

Wang, Zitong ; Kang, Peng ; Wu, Zewei et al. / A density-based clustering algorithm with educational applications. Current Developments in Web Based Learning - ICWL 2015 International Workshops, KMEL, IWUM, LA, Revised Selected Papers. editor / Di Zou ; Zhiguo Gong ; Dickson K.W. Chiu. 2016. pp. 118-127 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{9b9f8c05488e4cdea04ee8b06928b3f5,

title = "A density-based clustering algorithm with educational applications",

abstract = "With the rapid development of Web 2.0 and interactive technologies, learning resources are proliferating online. Confronting such large volume of educational data, users require effective and efficient methodologies to organize and manage them, which reveals the importance of clustering. In this paper, we first propose a method to estimate the data density, and then apply it to merge learning resources. The proposed algorithm estimates the confidence of any two learning resources to be a pair of neighbors, and conducts clustering by combining the above confidence with the similarities among resources. Experiments are designed to evaluate the performance of our algorithm using the standard clustering datasets. We also demonstrate how to employ the proposed algorithm in educational applications, including e-learner grouping, resource recommendation and usage patterns discovery.",

keywords = "Clustering analysis, Data density, E-learning, User modeling",

author = "Zitong Wang and Peng Kang and Zewei Wu and Yanghui Rao and Wang, \{Fu Lee\}",

note = "Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2016.; International Conference on Web Based Learning, ICWL 2015 ; Conference date: 05-11-2015 Through 08-11-2015",

year = "2016",

doi = "10.1007/978-3-319-32865-2\_13",

language = "English",

isbn = "9783319328645",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

pages = "118--127",

editor = "Di Zou and Zhiguo Gong and Chiu, \{Dickson K.W.\}",

booktitle = "Current Developments in Web Based Learning - ICWL 2015 International Workshops, KMEL, IWUM, LA, Revised Selected Papers",

}

Wang, Z, Kang, P, Wu, Z, Rao, Y & Wang, FL 2016, A density-based clustering algorithm with educational applications. in D Zou, Z Gong & DKW Chiu (eds), Current Developments in Web Based Learning - ICWL 2015 International Workshops, KMEL, IWUM, LA, Revised Selected Papers. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 9584 LNCS, pp. 118-127, International Conference on Web Based Learning, ICWL 2015, Guangzhou, China, 5/11/15. https://doi.org/10.1007/978-3-319-32865-2_13

A density-based clustering algorithm with educational applications. / Wang, Zitong; Kang, Peng; Wu, Zewei et al.
Current Developments in Web Based Learning - ICWL 2015 International Workshops, KMEL, IWUM, LA, Revised Selected Papers. ed. / Di Zou; Zhiguo Gong; Dickson K.W. Chiu. 2016. p. 118-127 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9584 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - A density-based clustering algorithm with educational applications

AU - Wang, Zitong

AU - Kang, Peng

AU - Wu, Zewei

AU - Rao, Yanghui

AU - Wang, Fu Lee

N1 - Publisher Copyright: © Springer International Publishing Switzerland 2016.

PY - 2016

Y1 - 2016

N2 - With the rapid development of Web 2.0 and interactive technologies, learning resources are proliferating online. Confronting such large volume of educational data, users require effective and efficient methodologies to organize and manage them, which reveals the importance of clustering. In this paper, we first propose a method to estimate the data density, and then apply it to merge learning resources. The proposed algorithm estimates the confidence of any two learning resources to be a pair of neighbors, and conducts clustering by combining the above confidence with the similarities among resources. Experiments are designed to evaluate the performance of our algorithm using the standard clustering datasets. We also demonstrate how to employ the proposed algorithm in educational applications, including e-learner grouping, resource recommendation and usage patterns discovery.

AB - With the rapid development of Web 2.0 and interactive technologies, learning resources are proliferating online. Confronting such large volume of educational data, users require effective and efficient methodologies to organize and manage them, which reveals the importance of clustering. In this paper, we first propose a method to estimate the data density, and then apply it to merge learning resources. The proposed algorithm estimates the confidence of any two learning resources to be a pair of neighbors, and conducts clustering by combining the above confidence with the similarities among resources. Experiments are designed to evaluate the performance of our algorithm using the standard clustering datasets. We also demonstrate how to employ the proposed algorithm in educational applications, including e-learner grouping, resource recommendation and usage patterns discovery.

KW - Clustering analysis

KW - Data density

KW - E-learning

KW - User modeling

UR - https://www.scopus.com/pages/publications/84981263341

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DO - 10.1007/978-3-319-32865-2_13

M3 - Conference contribution

AN - SCOPUS:84981263341

SN - 9783319328645

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 118

EP - 127

BT - Current Developments in Web Based Learning - ICWL 2015 International Workshops, KMEL, IWUM, LA, Revised Selected Papers

A2 - Zou, Di

A2 - Gong, Zhiguo

A2 - Chiu, Dickson K.W.

T2 - International Conference on Web Based Learning, ICWL 2015

Y2 - 5 November 2015 through 8 November 2015

ER -

Wang Z, Kang P, Wu Z, Rao Y, Wang FL. A density-based clustering algorithm with educational applications. In Zou D, Gong Z, Chiu DKW, editors, Current Developments in Web Based Learning - ICWL 2015 International Workshops, KMEL, IWUM, LA, Revised Selected Papers. 2016. p. 118-127. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-32865-2_13

A density-based clustering algorithm with educational applications

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Keywords

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