Paper: Semantic Structure from Correspondence Analysis

ACL ID W08-2007
Title Semantic Structure from Correspondence Analysis
Venue Coling 2008: Proceedings of the workshop on Speech Processing for Safety Critical Translation and Pervasive Applications
Year 2008

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.