Class-based n-gram models of natural language
Computational Linguistics
Building a large annotated corpus of English: the penn treebank
Computational Linguistics - Special issue on using large corpora: II
Distributional part-of-speech tagging
EACL '95 Proceedings of the seventh conference on European chapter of the Association for Computational Linguistics
Combining distributional and morphological information for part of speech induction
EACL '03 Proceedings of the tenth conference on European chapter of the Association for Computational Linguistics - Volume 1
Clustering polysemic subcategorization frame distributions semantically
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
Inducing syntactic categories by context distribution clustering
ConLL '00 Proceedings of the 2nd workshop on Learning language in logic and the 4th conference on Computational natural language learning - Volume 7
Contrastive estimation: training log-linear models on unlabeled data
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Introduction to Information Retrieval
Introduction to Information Retrieval
An incremental bayesian model for learning syntactic categories
CoNLL '08 Proceedings of the Twelfth Conference on Computational Natural Language Learning
Representations for category disambiguation
COLING '08 Proceedings of the 22nd International Conference on Computational Linguistics - Volume 1
Evaluating unsupervised part-of-speech tagging for grammar induction
COLING '08 Proceedings of the 22nd International Conference on Computational Linguistics - Volume 1
| Hi-index | 0.00 |
Building on the use of local contexts, or frames, for human category acquisition, we explore the treatment of contexts as categories. This allows us to examine and evaluate the categorical properties that local unsupervised methods can distinguish and their relationship to corpus POS tags. From there, we use lexical information to combine contexts in a way which preserves the intended category, providing a platform for grammatical category induction.