In this paper we investigated the usefulness of heterogeneous information sources in improving measures of semantic word relatedness.
we created vector space models using 4 data sources from 3 categories (corpus-based, Web-based and thesaurus-based) and found that simply averaging the cosine similarity derived from these models yields a very robust measure.