Machine Learning for Natural Languages Processing
published: Aug. 5, 2010, recorded: July 2010, views: 510
Report a problem or upload filesIf you have found a problem with this lecture or would like to send us extra material, articles, exercises, etc., please use our ticket system to describe your request and upload the data.
Enter your e-mail into the 'Cc' field, and we will keep you updated with your request's status.
Probabilistic Context Free Grammars (PCFG) is a powerful formalism that has been used for several applications in Computational Linguistics. One important problem of these models is the probabilistic estimation of the probabilistic part of the models. This probabilistic estimation is based on tabular algorithms similar to the CKY algorithm. We review these estimation algorithms and their properties. The use of these models for Language Modeling and Machine Translation is also introduced. Finally, an interactive-predictive framework for parsing is explained, that can be used for developing both on-line learning techniques and active learning techniques.
Link this pageWould you like to put a link to this lecture on your homepage?
Go ahead! Copy the HTML snippet !