Using sequential pattern mining to analyze the behavior on the WELS

Yi Lin Wang; Ling-Yu Wen; Tung Shou Chen; Rong Chang Chen

doi:10.1007/978-3-642-29084-8_15

Using sequential pattern mining to analyze the behavior on the WELS

Yi Lin Wang, Ling-Yu Wen, Tung Shou Chen, Rong Chang Chen

Department of Finance

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

1 Citation (Scopus)

Abstract

Sequential pattern mining is an important data-mining method for determining time-related behavior in sequence database. This study used the methods of Sequential Pattern Mining to design a system, which was to mine the browsing behavior on the web-based e-learning system (WELS) in two semesters of the college students from a national university in Taiwan. This study also segmented and mined the materials with three attributes as different, during midterm and final tests, the beginning, middle, end of the semester, and college. Through the results of mining, we hope we can provide website designers, teachers, and website managers advice on designing, teaching and managing.

Original language	English
Title of host publication	Information and Business Intelligence - International Conference, IBI 2011, Proceedings
Pages	95-101
Number of pages	7
Edition	PART 1
DOIs	https://doi.org/10.1007/978-3-642-29084-8_15
Publication status	Published - 2012 May 14
Event	International Conference on Information and Business Intelligence, IBI 2011 - Chongqing, China Duration: 2011 Dec 23 → 2011 Dec 25

Publication series

Name	Communications in Computer and Information Science
Number	PART 1
Volume	267 CCIS
ISSN (Print)	1865-0929

Other

Other	International Conference on Information and Business Intelligence, IBI 2011
Country	China
City	Chongqing
Period	11-12-23 → 11-12-25

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All Science Journal Classification (ASJC) codes

Computer Science(all)
Mathematics(all)

Cite this

Wang, Y. L., Wen, L-Y., Chen, T. S., & Chen, R. C. (2012). Using sequential pattern mining to analyze the behavior on the WELS. In Information and Business Intelligence - International Conference, IBI 2011, Proceedings (PART 1 ed., pp. 95-101). (Communications in Computer and Information Science; Vol. 267 CCIS, No. PART 1). https://doi.org/10.1007/978-3-642-29084-8_15

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abstract = "Sequential pattern mining is an important data-mining method for determining time-related behavior in sequence database. This study used the methods of Sequential Pattern Mining to design a system, which was to mine the browsing behavior on the web-based e-learning system (WELS) in two semesters of the college students from a national university in Taiwan. This study also segmented and mined the materials with three attributes as different, during midterm and final tests, the beginning, middle, end of the semester, and college. Through the results of mining, we hope we can provide website designers, teachers, and website managers advice on designing, teaching and managing.",

author = "Wang, {Yi Lin} and Ling-Yu Wen and Chen, {Tung Shou} and Chen, {Rong Chang}",

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Wang, YL, Wen, L-Y, Chen, TS & Chen, RC 2012, Using sequential pattern mining to analyze the behavior on the WELS. in Information and Business Intelligence - International Conference, IBI 2011, Proceedings. PART 1 edn, Communications in Computer and Information Science, no. PART 1, vol. 267 CCIS, pp. 95-101, International Conference on Information and Business Intelligence, IBI 2011, Chongqing, China, 11-12-23. https://doi.org/10.1007/978-3-642-29084-8_15

Using sequential pattern mining to analyze the behavior on the WELS. / Wang, Yi Lin; Wen, Ling-Yu; Chen, Tung Shou; Chen, Rong Chang.

Information and Business Intelligence - International Conference, IBI 2011, Proceedings. PART 1. ed. 2012. p. 95-101 (Communications in Computer and Information Science; Vol. 267 CCIS, No. PART 1).

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

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Access to Document

10.1007/978-3-642-29084-8_15