Distributional representations of words have been successfully used in many language processing tasks such as entity set expansion (Pantel et al., 2009), part-of-speech (POS) tagging and chunking (Huang and Yates, 2009), ontology learning (Curran, 2005), computing semantic textual similarity (Besançon et al., 1999), and lexical inference (Kotlerman et al., 2012).
the distribution of a word often varies from one domain 1 to another.