Abstract
In this paper we propose a novel framework using features extracted from Wikipedia for the task of matching named entities. We present how the employed features are extracted from Wikipedia and how its structure is utilized. We describe how a term-concepts table constructed from Wikipedia and the redirect links are integrated in the framework. In addition, the internal links within Wikipedia along with the categories structure are also used to compute the relatedness between concepts. We evaluate the built framework and report its performance in the applications of word sense disambiguation and named entities matching. The system performance is compared against other learning-based state-of-the-art systems and its reported results are found to be competitive. We also present a method in this paper for named entities matching that is context-independent and compare its results with those of other systems.