Knowledge representation: logical, philosophical and computational foundations
Knowledge representation: logical, philosophical and computational foundations
Usage patterns of collaborative tagging systems
Journal of Information Science
HT06, tagging paper, taxonomy, Flickr, academic article, to read
Proceedings of the seventeenth conference on Hypertext and hypermedia
MICAI'10 Proceedings of the 9th Mexican international conference on Advances in artificial intelligence: Part I
CROKODIL: a platform for collaborative resource-based learning
EC-TEL'11 Proceedings of the 6th European conference on Technology enhanced learning: towards ubiquitous learning
Automatic identification of tag types in a resource-based learning scenario
EC-TEL'11 Proceedings of the 6th European conference on Technology enhanced learning: towards ubiquitous learning
Ranking resources in folksonomies by exploiting semantic information
Proceedings of the 12th International Conference on Knowledge Management and Knowledge Technologies
Context determines content: an approach to resource recommendation in folksonomies
Proceedings of the 4th ACM RecSys workshop on Recommender systems and the social web
Exploiting semantic information for graph-based recommendations of learning resources
EC-TEL'12 Proceedings of the 7th European conference on Technology Enhanced Learning
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The web is increasingly used as an information source to gain new knowledge but the management of found web pages can be a challenging task. Often social tagging systems are used for resource management. Besides the obvious use of tags --- organizing a collection of web resources --- they support functionalities like sharing resources with other users and recommendation of further possibly relevant web pages. This paper describes a novel application based on an extended tagging concept that can improve resource management and recommendation. Adding semantic information to tags and tagging fragments of web pages instead of whole web pages enhance the possibilities of well-known tagging applications. Individual knowledge networks are the basis of this tagging concept. A first prototype is developed as proof of concept.