Semantic relatedness hits bibliographic data

In this paper we introduce a novel approach for the thematic organization of bibliographic records that builds upon a semantic relatedness measure we have implemented for this task. In particular, we introduce the Omiotis measure, which captures the semantic relatedness between text segments and enables the thematic organization of the bibliographic data stored in online databases. Experimental evaluation demonstrates that Omiotis can significantly improve the performance of several data mining tasks, such as publications' classification and clustering, compared to existing approaches; even when considering a limited amount of information, i.e., the paper titles.