Intent Classification in Question-Answering Using LSTM Architectures
Intent Classification in Question-Answering Using LSTM Architectures
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Ithaca: Cornell University Library, arXiv.org
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Language
English
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Publisher
Ithaca: Cornell University Library, arXiv.org
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Contents
Question-answering (QA) is certainly the best known and probably also one of the most complex problem within Natural Language Processing (NLP) and artificial intelligence (AI). Since the complete solution to the problem of finding a generic answer still seems far away, the wisest thing to do is to break down the problem by solving single simpler pa...
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Intent Classification in Question-Answering Using LSTM Architectures
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TN_cdi_proquest_journals_2347070111
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https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2347070111
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E-ISSN
2331-8422
DOI
10.48550/arxiv.2001.09330
