Jumping NLP Curves: A Review of Natural Language Processing Research

被引:583
|
作者
Cambria, Erik [1 ]
White, Bebo [2 ]
机构
[1] Nanyang Technol Univ, Sch Comp Engn, Singapore, Singapore
[2] Stanford Univ, SLAC Natl Accelerator Lab, Stanford, CA 94305 USA
关键词
MODEL; EVOLUTIONARY; LOGIC;
D O I
10.1109/MCI.2014.2307227
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Natural language processing (NLP) is a theory-motivated range of computational techniques for the automatic analysis and representation of human language. NLP research has evolved from the era of punch cards and batch processing (in which the analysis of a sentence could take up to 7 minutes) to the era of Google and the likes of it (in which millions of webpages can be processed in less than a second). This review paper draws on recent developments in NLP research to look at the past, present, and future of NLP technology in a new light. Borrowing the paradigm of 'jumping curves' from the field of business management and marketing prediction, this survey article reinterprets the evolution of NLP research as the intersection of three overlapping curves-namely Syntactics, Semantics, and Pragmatics Curves- which will eventually lead NLP research to evolve into natural language understanding.
引用
收藏
页码:48 / 57
页数:10
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