Paper: A Classification Approach To Word Prediction

ACL ID A00-2017
Title A Classification Approach To Word Prediction
Venue Annual Conference of the North American Chapter of the Association for Computational Linguistics
Session Main Conference
Year 2000

The eventual goal of a language model is to accu- rately predict the value of a missing word given its context. We present an approach to word prediction that is based on learning a representation for each word as a function of words and linguistics pred- icates in its context. This approach raises a few new questions that we address. First, in order to learn good word representations it is necessary to use an expressive representation of the context. We present a way that uses external knowledge to gener- ate expressive context representations, along with a learning method capable of handling the large num- ber of features generated this way that can, poten- tially, contribute to each prediction. Second, since the number of words "competing" for each predic- tion is large, there is a need...