Abstract

A common problem for clustering tech- niques is that clusters overlap, which makes graphing the statistical structure in the data difficult. A related problem is that we often want to see the distribution of factors (variables) as well as classes (objects). Correspondence Analysis (CA) offers a solution to both these problems. The structure that CA discovers may be an important step in representing similarity. We have performed an analysis for Italian verbs and nouns, and confirmed that simi- lar structures are found for English.

Citation information

McGillivray, B., Johansson, C., and Apollon, D. (2008). Semantic structure from Correspondence Analysis. In Proceedings of the Workshop on Graph-based Algorithms for Natural Language Processing (COLING 2008), Manchester

Turing affiliated authors