Paper: Collocation Extraction beyond the Independence Assumption

ACL ID P10-2020
Title Collocation Extraction beyond the Independence Assumption
Venue Annual Meeting of the Association of Computational Linguistics
Session Short Paper
Year 2010
Authors

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