A Classifying and Exploring System Based on Users' Tagging Behaviors
Nowadays, as information explosion, it becomes increasingly important for users to find a resource fast and efficiently in social tagging systems. To deal with the problem, this paper constructs an information classifying and exploring system based on users' tagging behaviors. We group the tags and resources by their semantic relations to construct Tag Bundles automatically, and generate a suitable category name for each group according to our category knowledge database, which generated by the open web information resources. Meanwhile, the system allows users to browse their interests by the histogram and analyze their interests' changing. Finally, we build a prototype system to validate the effectiveness of the proposed method.