Unsupervised Learning of Probabilistic Context-Free Grammar using Iterative Biclustering (Extended Version)
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Tu, Kewei and Honavar, Vasant (2008) Unsupervised Learning of Probabilistic Context-Free Grammar using Iterative Biclustering (Extended Version). Technical Report, Computer Science, Iowa State University.
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Abstract
This paper presents an unsupervised algorithm that learns a probabilistic context-free grammar from positive sample sentences only. The algorithm iteratively learns new grammar rules by doing biclustering in a table that enumerates all the symbol pairs in the training corpus. We explain our algorithm in a Bayesian framework, showing that it tries to find grammar rules that maximize the posterior of the grammar given the training corpus. Positive results were obtained in experiments.
| Keywords: | Probabilistic context-free grammar, grammar induction, grammar learning |
| Subjects: | Computing Methodologies: ARTIFICIAL INTELLIGENCE: Learning (K.3.2) |
| ID code: | 00000572 |
| Deposited by: | Kewei Tu |
Available Versions of This Paper
- Unsupervised Learning of Probabilistic Context-Free Grammar using Iterative Biclustering (Extended Version) (deposited 18 May 2008) [Currently displayed]
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