The Advent of Rule-Based Systems
The 1960’s and 1970’s witnessed the emergence of rule-primarily based systems inside the realm of NLP. Collaborations among linguists and computer scientists precipitated the development of structures that trusted predefined policies to analyze and understand human language.
The aim became to codify linguistic recommendations, at the side of syntax and grammar, into algorithms that would be completed by way of computer systems to machine and generate human-like text.
During this period, the General Problem Solver (GPS) received prominence. They had been developed with the resources of Allen Newell and Herbert A. Simon; in 1957, GPS wasn’t explicitly designed for language processing. However, it established the functionality of rule-based total systems by showcasing how computers must solve issues with the use of predefined policies and heuristics.
History and Evolution of NLP
As we know Natural language processing (NLP) is an exciting area that has grown at some stage in time, influencing the junction of linguistics, synthetic intelligence (AI), and computer technology knowledge.
This article takes you on an in-depth journey through the history of NLP, diving into its complex records and monitoring its development. From its early beginnings to the contemporary improvements of NLP, the story of NLP is an intriguing one that continues to revolutionize how we interact with generations.
History of Natural Language Processing (NLP)
- The Dawn of NLP (1950s-1970s)
- The Statistical Revolution (1980s-1990s)
- The Deep Learning Era (2000s-Present)
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