In this paper, we propose an unsupervised methodology to automatically discover pairs of semantically related words by highlighting their
local environment and evaluating their semantic similarity in local and global
semantic spaces. This proposal di®ers from previous research as it tries to take
the best of two different methodologies i.e. semantic space models and information extraction models. It can be applied to extract close semantic relations,
it limits the search space and it is unsupervised.