THE EFFECTIVENESS OF NATURAL LANGUAGE PROCESSING (NLP) AS A PROCESSING SOLUTION AND SEMANTIC IMPROVEMENT
The discussion in this paper shows that natural language processing helps computers communicate with humans in their own language and makes scaling other language-related tasks easier and more systematic.
Abstract
The purpose of writing this article is to discuss the function of Natural Language Processing (NLP) in semantic improvement. The writing method uses literature related to NLP on semantic processing and refinement. The discussion in this paper shows that natural language processing helps computers communicate with humans in their own language and makes scaling other language-related tasks easier and more systematic. Because NLP includes lexical/scanner analysis, syntactic/parser analysis, semantic/translator analysis and pragmatic/evaluator analysis. Each component is a sequence of interrelated processes and requires a knowledge base to process a language. Lexical analysis requires knowledge of vocabulary (lexicon) to understand word formation. Syntax analysis requires knowledge of grammar rules (grammar) to understand the structure of a sentence. Semantic analysis requires knowledge of the meaning and meaning of words to understand the relationship between words and the meaning of a sentence. Pragmatic analysis requires knowledge of a concept to understand the relationship between language and the context in which it is used.