Towards Computational Guessing of Unknown Word Meanings: The Ontological Semantic Approach

Abstract

The paper describes a computational approach for guessing the meanings of previously unaccounted words in an implemented system for natural language processing. Interested in comparing the results to what is known about human guessing, it reviews a largely educational approach, partially based on cognitive psychology, to teaching humans, mostly children, to acquire new vocabulary from contextual clues, as well as the lexicographic efforts to account for neologisms. It then goes over the previous NLP efforts in processing new words and establishes the difference—mostly, much richer semantic resources—of the proposed approach. Finally, the results of a computer experiment that guesses the meaning of a non-existent word, placed as the direct object of 100 randomly selected verbs, from the known meanings of these verbs, with methods of the ontological semantics technology, are presented and discussed. While the results are promising percentage-wise, ways to improve them within the approach are briefly outlined.


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