natural language processing


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natural language processing

[′nach·rəl ¦laŋ·gwij ′prä‚ses·iŋ]
(computer science)
Computer analysis and generation of natural language text; encompasses natural language interaction and natural language text processing.

Natural language processing

Computer analysis and generation of natural language text. The goal is to enable natural languages, such as English, French, or Japanese, to serve either as the medium through which users interact with computer systems such as database management systems and expert systems (natural language interaction), or as the object that a system processes into some more useful form such as in automatic text translation or text summarization (natural language text processing).

In the computer analysis of natural language, the initial task is to translate from a natural language utterance, usually in context, into a formal specification that the system can process further. Further processing depends on the particular application. In natural language interaction, it may involve reasoning, factual data retrieval, and generation of an appropriate tabular, graphic, or natural language response. In text processing, analysis may be followed by generation of an appropriate translation or a summary of the original text, or the formal specification may be stored as the basis for more accurate document retrieval later. Given its wide scope, natural language processing requires techniques for dealing with many aspects of language, in particular, syntax, semantics, discourse context, and pragmatics.

The first aspect of natural language processing, and the one that has perhaps received the most attention, is syntactic processing, or parsing. Syntactic processing is important because certain aspects of meaning can be determined only from the underlying structure and not simply from the linear string of words. A second phase of natural language processing, semantic analysis, involves extracting context-independent aspects of a sentence's meaning. Given that most natural languages allow people to take advantage of discourse context, their mutual beliefs about the world, and their shared spatio-temporal context to leave things unsaid or say them with minimal effort, the purpose of a third phase of natural language processing, contextual analysis, is to elaborate the semantic representation of what has been made explicit in the utterance with what is implicit from context. A fourth phase of natural language processing, pragmatics, takes into account the speaker's goal in uttering a particular thought in a particular way—what the utterance is being used to do.

natural language processing

(artificial intelligence)
(NLP) Computer understanding, analysis, manipulation, and/or generation of natural language.

This can refer to anything from fairly simple string-manipulation tasks like stemming, or building concordances of natural language texts, to higher-level AI-like tasks like processing user queries in natural language.
References in periodicals archive ?
Application of natural language processing to chemical patents.
The majority of practical applications of natural language processing technology are in interfacing with databases.
ATRANS, a commercial product, and ELOISE, a system developed as an exploratory project for the Securities and Exchange Commission, are examples of natural language processing applications in acquiring knowledge from texts.
In 1985, during the pilot test of the EDGAR system, a subsystem was implemented using natural language processing technology to read the text of proxy statements and index the documents as an aid to subsequent analysis.
Given the nature of accounting work and the current capabilities of natural language processing technology, five applications are likely to become common in the future.
Dictaphone is the leading provider of dictation, transcription, speech recognition and natural language processing systems in the healthcare market, and is also the leading provider of highly scalable dictation systems focused upon the public safety and legal markets.
The Rosette Linguistics Platform uses advanced natural language processing techniques to enable applications such as unstructured data management, document exploitation, business intelligence and text mining for global markets.
InFact is designed to enable professional analysts and researchers, who have long been frustrated by the inaccuracy and limitations of keyword search and early generation natural language processing search, to accurately uncover facts and relationships within text documents.
Introduced just this past July, mdEssential is the first software designed to automate the clinical documentation process in clinic and physician group practice settings through a combination of voice dictation, speech recognition and natural language processing (NLP) technologies.

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