Towards Graph-Based Recommendations for Resource-Based Learning using Semantic Tag Types
Key: ABR11-1
Author: Mojisola Anjorin, Doreen Böhnstedt, Christoph Rensing
Date: September 2011
Kind: In proceedings
Publisher: TUD press
Book title: DeLFI 2011: Die 9. e-Learning Fachtagung Informatik - Poster Workshops Kurzbeiträge
Abstract: Nearly everyone learns about new topics by searching on the Internet to be able to solve a specific task at work. Semantic tagging technologies and recommender systems can be used to support this form of resource-based learning on the Internet by suggesting similar or related resources and tags. In this paper, an approach is proposed explaining how the semantic tagging structure can be used to enhance the potential of graph-based recommendations by introducing a weighting concept based on semantic tag types.
View Full paper (PDF) | Download Full paper (PDF)

The documents distributed by this server have been provided by the contributing authors as a means to ensure timely dissemination of scholarly and technical work on a non-commercial basis. Copyright and all rights therein are maintained by the authors or by other copyright holders, not withstanding that they have offered their works here electronically. It is understood that all persons copying this information will adhere to the terms and constraints invoked by each author's copyright. These works may not be reposted without the explicit permission of the copyright holder.