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Applied Natural Language Processing

Applied Natural Language Processing

Gavagai has built an unsupervised and self-learning system that understands and continuously learns from streaming unstructured language/text data.

Our approach solves some of the most important problems in language technology: the variability problem, the out-of-vocabulary problem, and the problem of many languages that is, the possibility of using different words or expressions to communicate the same idea, the problem of terms encountered in input which are not present in a system's dictionary or database of known terms, and the problem that English is only one of many languages, respectively. Gavagai’s scalable approach to these problems is necessary for dealing with real world NLP applications.

Kyle Tenn

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Worked in Banking and Government. Studied at University of Toronto and Political Science Institute of Paris. Loving the freshness in Sweden.

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