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NATURAL LANGUAGE PROCESSING (NLP)
A method of communicating with an…
NATURAL LANGUAGE PROCESSING (NLP)
A method of communicating with an intelligent system using a natural language such as English.
Challenges
Semantics: the branch of linguistics and logic concerned with the analysis of word meanings and relations between them and deals with matters such as sense and reference and presupposition and implication, and lexical semantics
Morphology: the study of words, how they are formed, and their relationship to other words in the same language and also deals with the structure of words and parts of words, such as stems, root words, prefixes, and suffixes
Lexicon: a catalog of a language's words that deals with a system of rules which allow for the combination of those words into meaningful sentences
Syntactic: deals with the formal relations between signs or expressions in abstraction from their signification and their interpreters
Phonology: deals the system of contrastive relationships among the speech sounds that constitute the fundamental components of a language
Discourse Analysis: deals with the method of analyzing the structure of texts or utterances longer than one sentence
Pragmatics: deals with language in use and the contexts in which it is used, including such matters as deixis, the taking of turns in conversation, text organization, presupposition, and implicature.
Components
Natural Language Understanding: a branch of artificial intelligence (AI) that uses computer software to understand input made in the form of sentences in text or speech format
Natural Language Generation: the natural language processing task of generating natural language from a machine representation system such as a knowledge base or a logical form
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Applications
Machine Translation: a sub-field of computational linguistics that translates text or speech from one language to another
Caption Generation: understanding the content of the image to turn the understanding of the image into generation of words in the right order
Speech Recognition: the inter-disciplinary sub-field of computational linguistics that develops methodologies and technologies that enables the recognition and translation of spoken language into text
Language Modeling: probability distribution over sequences of words used in speech recognition, machine translation, part-of-speech tagging, parsing, handwriting recognition, information retrieval and other applications
Text Classification: categorize the subject matter, idea and concept of a document
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Question Answering: a computer science discipline within the fields of information retrieval which is concerned with building systems that automatically answer questions posed by humans in a natural language
History
1960s: ELIZA - an early natural language processing computer program created at the MIT Artificial Intelligence Laboratory by Joseph Weizenbaum to demonstrate the superficiality of communication between humans and machines
1970s: Conceptual Ontologies - study of the nature of being, becoming, existence, or reality, as well as the basic categories of being and their relations
1954: Georgetown–IBM experiment was an influential demonstration of machine translation which involved completely automatic translation of more than sixty Russian sentences into English
Until 1980s: complex hand-written programmed rules, then machine learning algorithms used
1950s: a seminal paper written by Alan Turing on the topic of artificial intelligence titled "Computing Machinery and Intelligence" was published to introduce his concept of what is now known as the Turing test to the general public.
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