Discriminating word senses with tourist walks in complex networks Supplementary Information
Thiago Christiano Silva, Diego R. Amancio · 2013
Patterns of topological arrangement is widely used for both animal and human brains in the learning process. Nevertheless, automatic learning techniques frequently overlook these patterns. In this paper, we apply a learning technique based on the structural organization of the data inn the attribute space to the problem of discrimination senses of 10 polysemous words. Using two types of characterization of meaning, namely semantical and topological approaches, we observed signicative accuracy rates in identifying the suitable meaning in both techniques. Most importantly, we found that the characterization based on the deterministic tourist walk improves the disambiguation process when one compares with the discrimination made with traditional complex networks measurements such as assortativity and clustering coecient. To