Foundations of statistical natural language processing
Foundations of statistical natural language processing
Class-Based Construction of a Verb Lexicon
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
Automatic retrieval and clustering of similar words
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 2
Measures of distributional similarity
ACL '99 Proceedings of the 37th annual meeting of the Association for Computational Linguistics on Computational Linguistics
Language independent authorship attribution using character level language models
EACL '03 Proceedings of the tenth conference on European chapter of the Association for Computational Linguistics - Volume 1
Co-occurrence Retrieval: A Flexible Framework for Lexical Distributional Similarity
Computational Linguistics
Characterising measures of lexical distributional similarity
COLING '04 Proceedings of the 20th international conference on Computational Linguistics
Individual and domain adaptation in sentence planning for dialogue
Journal of Artificial Intelligence Research
Towards personality-based user adaptation: psychologically informed stylistic language generation
User Modeling and User-Adapted Interaction
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Human text is characterised by the individual lexical choices of a specific author. Significant variations exist between authors. In contrast, natural language generation systems normally produce uniform texts. In this paper we apply distributional similarity measures to help verb choice in a natural language generation system which tries to generate text similar to individual author. By using a distributional similarity (DS) measure on corpora collected from a recipe domain, we get the most likely verbs for individual authors. The accuracy of matching verb pairs produced by distributional similarity is higher than using the synonym outputs of verbs from WordNet. Furthermore, the combination of the two methods provides the best accuracy.