Volume 10 Number 4 (Apr. 2015)
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JSW 2015 Vol.10(4): 392-402 ISSN: 1796-217X
doi: 10.17706/jsw.10.4.392-402

Learning Forum Posts Topic Discovery and Its Application in Recommendation System

Changri Luo1, Tingting He2*, Xinhua Zhang3, Zibo Zhou4
1National Engineering Research Center for e-Learning, Wuhan, China; College of Vocational and Continuing Education, Central China Normal University, Wuhan, China.
2Academy of Computer Science, Central China Normal University, Wuhan, China; Network Media Branch, National Language Resources Monitoring and Research Center, Wuhan, China.
3College of Computer ScienceWuhan Vocational College of Software and Engineering,Wuhan, China.
4College of Vocational and Continuing Education, Central China Normal University,Wuhan, China.


Abstract—What a network learner post on a network learning forum directly reflects the learners’ need during from the network learning process. The network learning supporting service could be greatly improved with mining topics from the forum posts. For this purpose, this paper employs the Learner-Topic (LT) model to mine learners’ posts and discover the topics. The results from the model are used to search the learners who have the same learning interest and recommend the learning resources in a recommendation system.

Index Terms—Network learner, topic model, LT model, post, recommendation.

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Cite: Changri Luo, Tingting He, Xinhua Zhang, Zibo Zhou, "Learning Forum Posts Topic Discovery and Its Application in Recommendation System," Journal of Software vol. 10, no. 4, pp. 392-402, 2015.

General Information

ISSN: 1796-217X (Online)
Frequency:  Bimonthly (Since 2020)
Editor-in-Chief: Prof. Antanas Verikas
Executive Editor: Ms. Yoyo Y. Zhou
Abstracting/ Indexing: DBLP, EBSCO, Google Scholar, ProQuest, INSPEC(IET), ULRICH's Periodicals Directory, WorldCat, etc
E-mail: jsw@iap.org
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