The Study on Educational Resources Based on the Recommended Services

Abstract:

In the network teaching system, with the increasing teaching resources, student resources are increasingly difficult to find interesting, so join teaching resource referral service in online teaching system allows students freed from the vast network of information resources, greatly saving time and effort spent on students in search of information. Under these conditions and needs, educational resources referral service technology has been progressively developed. This article is recommended for Educational Resources Services referral service model, resource feature representation and recommendation algorithm based on machine learning and other key technologies were discussed and studied.

• Periodical: Applied Mechanics and Materials (Volumes 687-691)
• Pages: 2411-2414
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.687-691.2411
• Online since: November 2014
• Authors: Wen Lu Li*
• Keywords: Active Learning, Distributed Learning, Educational Resource

References

[1] G. Adomavicius,A. Tuzhilin. Toward the Next Generation of Recommender Systems: A Survey of the State-of-the-Art and Possible Extensions，IEEE Trans, on Knowl. and Data Eng., vol. 17，iss. 6，pp.734-749，(2009).

DOI: 10.1109/tkde.2005.99

[2] M. Balabanovi,Y. Shoham. Learning Information Retrieval Agents: Experiments with Automated Web Browsing, in AAAI Spring Symposium on Information Gathering, pp.13-18, (2010).

[3] H. Lieberman. Letizia: An Agent That Assists Web Browsing, in Proceedings of the Fourteenth International Joint Conference on Artificial Intelligence, pp.924-929，(2012).

[4] M. Pazzani,J. Muramatsu，D. Billsus. Syskill&Webert: Identifying interesting web sites, presented at the Proceedings of the thirteenth national conference on Artificial intelligence-Volume 1，Portland，Oregon, (2012).

[5] Goldberg D, Nichols D, Oki B M, et al. Using Collaborative Filtering to Weave an Information Tapestry. Communications of the ACM, 2012, 35(12): 61~70.

DOI: 10.1145/138859.138867

[6] J.L. Herlocker J.A. Konstan，A. Borchers,J. Riedl. An algorithmic framework for performing collaborative filtering，presented at the Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval, Berkeley, California, United States, (2011).

DOI: 10.1145/312624.312682