Abstract
The amount of online courses and educational content available on the Internet is growing rapidly, leaving students with large and diverse number of choices for their areas of interest. The educational content is spread into diverse e-learning platforms, making its search and comparison even more challenging. Classifying educational content into a standardized set of academic disciplines or topics can improve its search, comparison and combination to better meet students’ inquiries. In this paper we make use of well-known techniques from Information Retrieval to map course descriptions into two common sets of topics, one manually created and well-controlled, i.e. CIP, and one collaboratively created, i.e. Wikipedia. We then analyze and compare the results to see how the size of the topic schemes and their associated data, such as textual descriptions, affect the accuracy of the end results.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
- 2.
- 3.
- 4.
- 5.
- 6.
- 7.
- 8.
- 9.
- 10.
- 11.
References
Apaza, R.G., Cervantes, E.V., Quispe, L.C., Luna, J.O.: Online courses recommendation based on lda. In: SIMBig, pp. 42–48 (2014)
Gasparetti, F., Limongelli, C., Sciarrone, F.: Exploiting wikipedia for discovering prerequisite relationships among learning objects. In: 2015 International Conference on Information Technology Based Higher Education and Training (ITHET), pp. 1–6. IEEE (2015)
Gjorgjevik, A., Stojanov, R., Trajanov, D.: Semccm: course and competence management in learning management systems using semantic web technologies. In: Proceedings of the 10th International Conference on Semantic Systems, pp. 140–147. ACM (2014)
Huang, A.: Similarity measures for text document clustering. In: Proceedings of the Sixth New Zealand Computer Science Research Student Conference (NZCSRSC2008), Christchurch, New Zealand, pp. 49–56 (2008)
Lehmann, J., Isele, R., Jakob, M., Jentzsch, A., Kontokostas, D., Mendes, P.N., Hellmann, S., Morsey, M., Van Kleef, P., Auer, S., et al.: Dbpedia–a large-scale, multilingual knowledge base extracted from wikipedia. Semant. Web 6(2), 167–195 (2015)
Limongelli, C., Gasparetti, F., Sciarrone, F.: Wiki course builder: a system for retrieving and sequencing didactic materials from wikipedia. In: 2015 International Conference on Information Technology Based Higher Education and Training (ITHET), pp. 1–6. IEEE (2015)
Manning, C.D., Raghavan, P., SchĂĽtze, H., et al.: Introduction to Information Retrieval, vol. 1. Cambridge University Press, Cambridge (2008)
Shatnawi, S., Gaber, M.M., Cocea, M.: Text stream mining for massive open online courses: review and perspectives. Syst. Sci. Control Eng. Open Access J. 2(1), 664–676 (2014)
Strehl, A., Ghosh, J., Mooney, R.: Impact of similarity measures on web-page clustering. In: Workshop on Artificial Intelligence for Web Search (AAAI 2000), vol. 58, p. 64 (2000)
Tam, V., Lam, E.Y., Fung, S.: A new framework of concept clustering and learning path optimization to develop the next-generation e-learning systems. J. Comput. Educ. 1(4), 335–352 (2014)
Xu, R.: Pos weighted tf-idf algorithm and its application for an mooc search engine. In: 2014 International Conference on Audio, Language and Image Processing (ICALIP), pp. 868–873. IEEE (2014)
Zhuhadar, L., Kruk, S.R., Daday, J.: Semantically enriched massive open online courses (moocs) platform. Comput. Hum. Behav. 51, 578–593 (2015)
Author information
Authors and Affiliations
Corresponding authors
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer International Publishing AG
About this paper
Cite this paper
Dimitrovski, A., Gjorgjevikj, A., Trajanov, D. (2017). Courses Content Classification Based on Wikipedia and CIP Taxonomy. In: Trajanov, D., Bakeva, V. (eds) ICT Innovations 2017. ICT Innovations 2017. Communications in Computer and Information Science, vol 778. Springer, Cham. https://doi.org/10.1007/978-3-319-67597-8_14
Download citation
DOI: https://doi.org/10.1007/978-3-319-67597-8_14
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-67596-1
Online ISBN: 978-3-319-67597-8
eBook Packages: Computer ScienceComputer Science (R0)