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Natural language processing (NLP) is an interdisciplinary subfield of computer science and information retrieval. It is primarily concerned with giving computers the ability to support and manipulate human language. It involves processing natural language datasets, such as text corpora or speech corpora, … See more
Natural language processing has its roots in the 1940s. Already in 1940, Alan Turing published an article titled "Computing Machinery and Intelligence" which proposed what is … See more
Symbolic approach, i.e., the hand-coding of a set of rules for manipulating symbols, coupled with a dictionary lookup, was historically the first … See more
Based on long-standing trends in the field, it is possible to extrapolate future directions of NLP. As of 2020, three trends among the topics of … See more
• Bates, M (1995). "Models of natural language understanding". Proceedings of the National Academy of Sciences of the United States of America. 92 (22): 9977–9982. Bibcode:1995PNAS...92.9977B. doi:
• Steven … See more1940sAlan Turing published an article titled "Computing Machinery and Intelligence" which proposed what is now called the Turing test as a criterion of intelligence, though at the time that was not articulated as a problem separate from artificial intelligence.1950sThe Georgetown experiment in 1954 involved fully automatic translation of more than sixty Russian sentences into English.1960sSome notably successful natural language processing systems developed in the 1960s were SHRDLU, a natural language system working in restricted "blocks worlds" with restricted vocabularies, and ELIZA, a simulation of a Rogerian psychotherapist, written by Joseph Weizenbaum between 1964 and 1966.1970sDuring the 1970s, many programmers began to write "conceptual ontologies", which structured real-world information into computer-understandable data.1980sThe 1980s and early 1990s mark the heyday of symbolic methods in NLP.1990sUp until the 1980s, most natural language processing systems were based on complex sets of hand-written rules. Starting in the late 1980s, however, there was a revolution in natural language processing with the introduction of machine learning algorithms for language processing.2000sWith the growth of the web, increasing amounts of raw (unannotated) language data has become available since the mid-1990s. Research has thus increasingly focused on unsupervised and semi-supervised learning algorithms.2003Word n-gram model, at the time the best statistical algorithm, was overperformed by a multi-layer perceptron (with a single hidden layer and context length of several words trained on up to 14 million of words with a CPU cluster in language modelling) by Yoshua Bengio with co-authors.2010sRepresentation learning and deep neural network-style (featuring many hidden layers) machine learning methods became widespread in natural language processing.The following is a list of some of the most commonly researched tasks in natural language processing. Some of these tasks have direct real-world applications, while others more commonly serve as subtasks that are used to aid in solving larger tasks. See more
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Wikipedia text under CC-BY-SA license WebMar 19, 2024 · Natural language processing (NLP) is a subset of artificial intelligence, computer science, and linguistics focused on making human communication, such as speech and text, comprehensible to computers. …
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WebJul 31, 2023 · NLP Use Cases. Deep learning and NLP. References. What is natural language processing? | Video: IBM Technology. What Is Natural Language Processing? Speech recognition — the translation of spoken …
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