Evaluation of Hierarchical Clustering via Markov Decision Processes for Efficient Navigation and Search

Raúl Moreno, Weipéng Huáng, Arjumand Younus, Michael P. O'Mahony, Neil J. Hurley

Abstract: In this paper, we propose a new evaluation measure to assess the quality of a hierarchy in supporting search queries to content collections. The evaluation measure models the scenario of a searcher seeking a particular target item in the hierarchy. It takes into account the structure of the hierarchy by measuring the cognitive challenge of determining the correct path in the hierarchy as well as the reduction in search time afforded by hierarchy. The goal is to propose a general-purpose measure that can be applied in different application contexts, allowing different hierarchical arrangements of content to be quantitatively assessed.