Labeling Clusters - Tagging Resources

In order to support the navigation in huge document collections efficiently, tagged hierarchical structures can be used. Often, multiple tags are used to describe resources. For users, it is important to correctly interpret such tag combinations. In this paper, we propose the usage of tag groups for addressing this issue and an algorithm that is able to extract these automatically for text documents. The approach is based on the diversity of content in a document collection and a user's structuring preference. For evaluation, we use methods from ontology evaluation and show the validity of our approach on a benchmark dataset. 1 Labeling vs. Tagging When searching for information, structured access to data, e.g., as given by web directories or social tagging systems like del.icio.us1 can be very helpful. The goal of our work is to automatically provide such structure for unstructured collections. Here, we consider text documents. One possible direction is to hierarchically cluster...

• Type: Conference
• Year: 2008
• Where: LWA
• Authors: Korinna Bade, Andreas Nürnberger
• Keywords: Document Collection, Documents, LWA 2008, Software Engineering, Text Documents