JUCS - Journal of Universal Computer Science 15(3): 678-691, doi: 10.3217/jucs-015-03-0678
Providing Multi Source Tag Recommendations in a Social Resource Sharing Platform
expand article infoMartin Memmel‡, Michael Kockler‡, Rafael Schirru§
‡ DFKI GmbH, Kaiserslautern, Germany§ University of Kaiserslautern, Kaiserslautern, Germany

Corresponding author: Martin Memmel ( memmel@dfki.de )

© Martin Memmel, Michael Kockler, Rafael Schirru.
This article is freely available under the J.UCS Open Content License.
Citation: Memmel M, Kockler M, Schirru R (2009) Providing Multi Source Tag Recommendations in a Social Resource Sharing Platform. JUCS - Journal of Universal Computer Science 15(3): 678-691. https://doi.org/10.3217/jucs-015-03-0678
Open Access
Abstract
In today's information environments, tagging is widely used to provide information about arbitrary types of digital resources. This information is usually 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. In this paper several approaches to generate tag recommendations are discussed, and a prototypical recommender system for the social resource sharing platform ALOE is 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.
Keywords
classification, collaborative tagging, digital resources, knowledge management, knowledge sharing, metadata, recommender, tagging, web 2.0