Topic Calculation and Clustering: An Application to Wikipedia

Abstract

Wikipedia is nowadays one of the most valuable information resources; nevertheless, its current structure, which has no formal organization, does not allow to always have a useful browsing among topics. Moreover, even though most Wikipedia pages include a "See Also" section for navigating through those articles' related Wikipedia pages, the only references included here are those which authors are aware of, leading to incompleteness and other irregularities. In this work, a method for finding related Wikipedia articles is proposed; this method relies on a framework that clusters documents into semantically-calculated topics and selects the closest documents which could enrich the "See Also" section.