Abstract
From e-commerce to social networking sites, recommender systems are gaining more and more interest. They provide connections, news, resources, or products of interest. This paper presents a federated recommender system, which exploits data from different online learning platforms and delivers personalized recommendation. The underlying educational objective is to enable academic institutions to provide a Web 2.0 dashboard bringing together open resources from the Cloud and proprietary content from in-house learning management systems. The paper describes the main aspects of the federated recommender system, including its adopted architecture, the common data model used to harvest the different learning platforms, the recommendation algorithm, as well as the recommendation display widget.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Guy, I., Jaimes, A., Agulló, P., Moore, P., Nandy, P., Nastar, C., Schinzel, H.: Will Recommenders Kill Search? Recommender Systems – an Industry Perspective. In: Proceedings of the 4th ACM Conference on Recommender Systems, pp. 7–12 (2010)
Manouselis, N., Drachsler, H., Vuorikari, R., Hummel, H., Koper, R.: Recommender Systems in Technology Enhanced Learning. In: Recommender Systems Handbook, Part 2, pp. 387–415 (2011)
Dabbagh, N., Kitsantas, A.: Personal Learning Environments, Social Media, and Self Regulated Learning: A Natural Formula for Connecting Formal and Informal Learning. The Internet and Higher Education 15, 3–8 (2012)
Tang, T.Y., Mccalla, G.: Smart Recommendation for an Evolving E-Learning System: Architecture and Experiment. International Journal on E-Learning 4, 105–129, http://www.editlib.org/p/5822 (retrieved March 2012)
LMS Installations 2010 at Swiss Institutions of Higher Education, http://eduhub.ch/info/lms-installations10.html (retrieved April 2012)
Drbálek, Z., Dulík, T., Koblischke, R.: Developing components for distributed search engine ObjectSpot. In: Proceedings of the 8th WSEAS International Conference on Distance Learning and Web Engineering, pp. 82–85 (2008)
Govaerts, S., El Helou, S., Duval, E., Gillet, D.: A Federated Search and Social Recommendation Widget. In: Proceedings of the 2nd International Workshop on Social Recommender Systems in conjunction with the 2011 ACM Conference on Computer Supported Cooperative Work, pp. 1–8 (2011)
Kaushik, S., Kollipalli, D.: Multi-Agent based Architecture for Querying Disjoint Data Repositories. In: International Conference on Machine and Web Intelligence, pp. 28–34 (2011)
Gil, A.B., De la Prieta, F., Rodríguez, S.: Automatic Learning Object Extraction and Classification in Heterogeneous Environments. In: Pérez, J.B., Corchado, J.M., Moreno, M.N., Julián, V., Mathieu, P., Canada-Bago, J., Ortega, A., Caballero, A.F. (eds.) Highlights in Practical Applications of Agents and Multiagent Systems. AISC, vol. 89, pp. 109–116. Springer, Heidelberg (2011)
Ternier, S., Verbert, K., Parra, G., Vandeputte, B., Klerkx, J., Duval, E., Ordoez, V., Ochoa, X.: The Ariadne Infrastructure for Managing and Storing Metadata. IEEE Internet Computing 13, 18–25 (2009)
Ha, K.-H., Niemann, K., Schwertel, U., Holtkamp, P., Pirkkalainen, H., Boerner, D., Kalz, M., Pitsilis, V., Vidalis, A., Pappa, D., Bick, M., Pawlowski, J., Wolpers, M.: A Novel Approach towards Skill-Based Search and Services of Open Educational Resources. In: García-Barriocanal, E., Cebeci, Z., Okur, M.C., Öztürk, A. (eds.) MTSR 2011. CCIS, vol. 240, pp. 312–323. Springer, Heidelberg (2011)
Grewe, L., Pandey, S.: Quantization of Social Data for Friend Advertisement Recommendation System. In: Nagamalai, D. (ed.) PDCTA 2011. CCIS, vol. 203, pp. 596–614. Springer, Heidelberg (2011)
El Helou, S., Li, N., Gillet, D.: The 3A interaction model: towards bridging the gap between formal and informal learning. In: Proceedings of the Third International Conferences on Advances in Computer-Human Interactions, pp. 179–184 (2010)
Page, L., Brin, S., Motwani, R., Winograd, T.: The PageRank citation ranking: Bringing order to the Web. Technical report. Stanford: Stanford Digital Library Technologies Project (1999)
El Helou, S., Salzmann, C., Gillet, D.: The 3A Personalized, Contextual and Relation based Recommender System. Journal of Universal Computer Science 16(16), 2179–2195 (2010)
Shibboleth Architecture Technical Overview, http://shibboleth.internet2.edu/docs/draft-mace-shibboleth-tech-overview-latest.pdf (retrieved March 2012)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Zhou, L. et al. (2012). A Federated Recommender System for Online Learning Environments. In: Popescu, E., Li, Q., Klamma, R., Leung, H., Specht, M. (eds) Advances in Web-Based Learning - ICWL 2012. ICWL 2012. Lecture Notes in Computer Science, vol 7558. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33642-3_10
Download citation
DOI: https://doi.org/10.1007/978-3-642-33642-3_10
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-33641-6
Online ISBN: 978-3-642-33642-3
eBook Packages: Computer ScienceComputer Science (R0)