Back فهم اللغات الطبيعية Arabic স্বাভাবিক ভাষা উপলব্ধি Bengali/Bangla Razumijevanje prirodnog jezika BS Comprensió del llenguatge natural Catalan Comprensión del lenguaje natural Spanish فهم زبانهای طبیعی Persian Compréhension du langage naturel French Բնական լեզվի գիտակցում Armenian Pemahaman bahasa alami ID 自然言語理解 Japanese
 | This article needs to be updated. The reason given is: lack of discussion of recent developments related to large language models, but also no mention of older techniques like word embedding or word2vec. (February 2024) |
Natural-language understanding (NLU) or natural-language interpretation (NLI)[1] is a subset of natural-language processing in artificial intelligence that deals with machine reading comprehension. Natural-language understanding is considered an AI-hard problem.[2]
There is considerable commercial interest in the field because of its application to automated reasoning,[3] machine translation,[4] question answering,[5] news-gathering, text categorization, voice-activation, archiving, and large-scale content analysis.
- ^ Semaan, P. (2012). Natural Language Generation: An Overview. Journal of Computer Science & Research (JCSCR)-ISSN, 50-57
- ^ Roman V. Yampolskiy. Turing Test as a Defining Feature of AI-Completeness . In Artificial Intelligence, Evolutionary Computation and Metaheuristics (AIECM) --In the footsteps of Alan Turing. Xin-She Yang (Ed.). pp. 3-17. (Chapter 1). Springer, London. 2013. http://cecs.louisville.edu/ry/TuringTestasaDefiningFeature04270003.pdf
- ^ Van Harmelen, Frank, Vladimir Lifschitz, and Bruce Porter, eds. Handbook of knowledge representation. Vol. 1. Elsevier, 2008.
- ^ Macherey, Klaus, Franz Josef Och, and Hermann Ney. "Natural language understanding using statistical machine translation." Seventh European Conference on Speech Communication and Technology. 2001.
- ^ Hirschman, Lynette, and Robert Gaizauskas. "Natural language question answering: the view from here." natural language engineering 7.4 (2001): 275-300.
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