Providing Multi Source Tag Recommendations in a Social Resource Sharing Platform

Martin Memmel; Michael Kockler; Rafael Schirru

In: Hermann Maurer; Frank Kappe; Werner Haas; Klaus Tochtermann (Hrsg.). Proceedings of I-KNOW '08 and I-MEDIA '08. International Conferences on Knowledge Management and New Media Technology (I-MEDIA-08), located at TRIPLE-I, September 3-5, Graz, Australia, Pages 226-233, Journal of Universal Computer Science (J.UCS), ISBN ISSN 0948-695x, Journal of Universal Computer Science, 9/2008.


In today's information environments, tagging is widely used to provide information about arbitrary types of digital resources.This information is created by end users with different motivations and for different kinds of purposes. When aiming to support users in the tagging process, these differences play an important role. This paper discusses several approaches to generate tag recommendations, and a prototypical recommender system for the social resource sharing platform ALOE will be presented. This interactive system allows users to control the generation of the recommendations by selecting the sources to be used as well as their impact. The component was introduced at DFKI, and a first evaluation showed that the recommender component was considered as helpful by a majority of users.


Deutsches Forschungszentrum für Künstliche Intelligenz
German Research Center for Artificial Intelligence