We propose a method for estimating the probability of such previously unseen word combinations using available information on “most similar” words.

1998/09/27 · In the language modeling task, a similarity-based model is used to improve probability estimates for unseen bigrams in a back-off language model ...

In this work we propose a method for estimating the probability of such previously unseen word combinations using available information on “most similar” words.

This work proposes a method for estimating the probability of such previously unseen word combinations using available information on “most similar” words, ...

We describe a probabilistic word association model based on distributional word similarity, and apply it to improving probability estimates for unseen word bi-.

Similarity-Based Models of Word Cooccurrence Probabilities. Ido Dagan. Lillian Lee. Fernando C. N. Pereira. Machine Learning, 34 (1999), pp. 43-69.

The similarity-based method yields a 20% perplexity improvement in the prediction of unseen bigrams and statistically significant reductions in speech- ...

A probabilistic word association model based on distributional word similarity is described, and it is applied to improving probability estimates for unseen ...

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Algorithms & Theory · Data Management · Data Mining & Modeling · Information ... Similarity-Based Estimation of Word Cooccurrence Probabilities. Ido Dagan.