User Oriented Hierarchical Information Organization and Retrieval

In order to organize huge document collections, labeled hierarchical structures are used frequently. Users are most efficient in navigating such hierarchies, if they reflect their personal interests. Thus, we propose in this article an approach that is able to derive a personalized hierarchical structure from a document collection. The approach is based on a semi-supervised hierarchical clustering approach, which is combined with a biased cluster extraction process. Furthermore, we label the clusters for efficient navigation. Besides the algorithms itself, we describe an evaluation of our approach using benchmark datasets.