In the future, we will apply CLGVSM in more languages pairs and extend it in more than two languages.
experimental results on benchmarking data set show that (1) the proposed CLGVSM is very effective for cross-document clustering, outperforming the two strong baselines vector space model (VSM) and latent semantic analysis (LSA) significantly; and (2) the new feature selection method can further improve CLGVSM.