Selection and information: a class-based approach to lexical relationships
Selection and information: a class-based approach to lexical relationships
Learning class-to-class selectional preferences
ConLL '01 Proceedings of the 2001 workshop on Computational Natural Language Learning - Volume 7
Inductive Dependency Parsing (Text, Speech and Language Technology)
Inductive Dependency Parsing (Text, Speech and Language Technology)
Semantic role labeling via FrameNet, VerbNet and PropBank
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
TextGraphs-1 Proceedings of the First Workshop on Graph Based Methods for Natural Language Processing
| Hi-index | 0.00 |
A common problem for clustering techniques 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 similar structures are found for English.