Collocation Extraction beyond the Independence Assumption

In this paper we start to explore two-part collocation extraction association measures that do not estimate expected probabilities on the basis of the independence assumption. We propose two new measures based upon the well-known measures of mutual information and pointwise mutual information. Expected probabilities are derived from automatically trained Aggregate Markov Models. On three collocation gold standards, we find the new association measures vary in their effectiveness.

• Type: Journal
• Year: 2010
• Where: ACL
• Authors: Gerlof Bouma
• Keywords: ACL 2010, Collocation Gold Standards, Computational Linguistics, Mutual Information, Two-part Collocation Extraction