Abstract
This paper discusses the rationale for the representation of user feedback in a structured and reusable format so that it can be reused by different recommender systems. We emphasize how information about the context can be included in such a representation. This work-in-progress takes place in the context of two large European initiatives that set up collections of digital educational resources in distributed repositories to serve the needs of different user communities, and to collect user feedback such as ratings, bookmarks and tags related to the resources. The overall aim is to facilitate the exchange and reuse of their data sets in order to support recommendation of appropriate resources to the end users.
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Herlocker, J., Konstan, J.A., Riedl, J.: An Empirical Analysis of Design Choices in Neighborhood-Based Collaborative Filtering Algorithms. Information Retrieval 5 (2002)
Herlocker, J.L., Konstan, J.A., Terveen, L.G., Riedl, J.T.: Evaluating Collaborative Filtering Recommender Systems. ACM Transactions on Information Systems 22(1), 5–53 (2004)
Vuorikari, R.: Can social information retrieval enhance the discovery and reuse of digital educational content? In: Proceedings of the 2007 ACM Conference on Recommender Systems. RecSys 2007, Minneapolis, MN, USA, October 19 - 20, 2007, pp. 207–210. ACM, New York (2007)
AttentionXML: AttentionXML specifications (2004), http://developers.technorati.com/wiki/attentionxml (Retrieved June 8, 2007)
Najjar, J., Wolpers, M., Duval, E.: Attention Metadata: Collection and Management. Paper presented at the World Wide Web 2006 Workshop Logging Traces of Web Activity: The Mechanics of Data Collection, Edinburgh, UK, May 23 (2006)
Vuorikari, R., Manouselis, N., Duval, E.: Using Metadata for Storing, Sharing, and Reusing Evaluations. In: Go, D.H., Foo, S. (eds.) Social Information Retrieval Systems: Emerging Technologies and Applications for Searching the Web Effectively, pp. 87–107. Idea Group Publishing, Hershey (2008)
Manouselis, N., Vuorikari, R., Van Assche, F.: Simulated Analysis of MAUT Collaborative Filtering for Learning Object Recommendation. In: Proc. of the Workshop on Social Information Retrieval for Technology-Enhanced Learning (SIRTEL 2007), 2nd European Conference on Technology Enhanced Learning, Crete, Greece (2007)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Manouselis, N., Vuorikari, R. (2009). What If Annotations Were Reusable: A Preliminary Discussion. In: Spaniol, M., Li, Q., Klamma, R., Lau, R.W.H. (eds) Advances in Web Based Learning – ICWL 2009. ICWL 2009. Lecture Notes in Computer Science, vol 5686. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03426-8_32
Download citation
DOI: https://doi.org/10.1007/978-3-642-03426-8_32
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-03425-1
Online ISBN: 978-3-642-03426-8
eBook Packages: Computer ScienceComputer Science (R0)