Providing Multi Source Tag Recommendations in a Social Resource Sharing Platform

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.