A Pattern Based Approach for the Derivation of Base Forms of Verbs from Participles and Tenses for Flexible NLP
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Abstract
Natural Language Processing (NLP) is an integral part of a conversation and by proxy an integral part of a chatterbot. Building a complete vocabulary for a chatterbot is a prohibitively time and effort intensive endeavor and thus makes a learning chatterbot a much more efficient alternative. Learning can be performed from many facets including individual words to phrases and concepts. From the perspective of words, the grammatical parts of speech become important since they allow meaning and structure to be derived from a sentence. Verbs tend to be unique since they have different forms, namely participles and tenses. As such we present an algorithm to derive the base verb from any participle or tense.
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Raj, R. G., & Abdul-Kareem, S. (2011). A Pattern Based Approach for the Derivation of Base Forms of Verbs from Participles and Tenses for Flexible NLP. Malaysian Journal of Computer Science, 24(2), 63–72. Retrieved from http://jice.um.edu.my/index.php/MJCS/article/view/6542
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