Feature Weighting for Co-occurrence-based Classification of Words

The paper comparatively studies methods of feature weighting in application to the task of cooccurrence-based classification of words according to their meaning. We explore parameter optimization of several weighting methods frequently used for similar problems such as text classification. We find that successful application of all the methods crucially depends on a number of parameters; only a carefully chosen weighting procedure allows to obtain consistent improvement on a classifier learned from non-weighted data.