Natural language understanding is a subtopic of natural language processing in artificial intelligence that deals with machine reading comprehension.
The process of disassembling and parsing input is more complex than the reverse process of assembling output in natural language generation because of the occurrence of unknown and unexpected features in the input and the need to determine the appropriate syntactic and semantic schemes to apply to it, factors which are pre-determined when outputting language.
There is considerable commercial interest in the field because of its application to news-gathering, text categorization, voice-activation, archiving and large-scale content-analysis.
Read more about Natural Language Understanding: History, Scope and Context, Components and Architecture
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