TagClouds are a popular visualization for collaboratively generated tags. However, they have some distinct problems such as linguistic issues, high semantic density and poor communication of hierarchical structure and semantic relationships among tags. In this paper we investigate ways to support semantic understanding of collaboratively generated tags beyond TagClouds. Following the results of a survey, we propose an improved visualization named TagClusters. Based on a semantic analysis, tags are clustered into different semantic groups. Their visual distance depends on the semantic similarity between tags, and thus the visualization offers a better semantic understanding of collaboratively generated tags. We conducted a comparative evaluation with TagClouds and TagClusters based on the same tag set. We received overall positive feedback on TagClusters and the results indicate that it has advantages in supporting efficient browsing, searching, impression formation and matching. In our future work, we will explore the possibilities of tag recommendation and tag-based Information Retrieval based on TagClusters
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