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Towards Graph-Based Recommendations for Resource-Based Learning using Semantic Tag Types

Key:ABR11
Author:Mojisola Anjorin, Doreen Böhnstedt, Christoph Rensing
Date:September 2011
Kind:In proceedings - use for conference & workshop papers
Publisher:TUD press
Address:Dresden
Book title:DeLFI 2011: Die 9. e-Learning Fachtagung Informatik - Poster Workshops Kurzbeiträge
Editor:Steffen Friedrich, Andrea Kienle, Holger Rohland
ISBN:9783942710367
Language:English
Number of characters:12481
Research Area(s):Knowledge Media
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.
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Prof. Dr.-Ing. Ralf Steinmetz

Technische Universität Darmstadt
Fachgebiet Multimedia Kommunikation
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64283 Darmstadt
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