Tokenization Process with NFA
NFA is a finite automaton where transitions from one state to another are non-deterministic, allowing multiple possible transitions for a given input symbol. NFA-based tokenization involves utilizing non-deterministic state machines to recognize patterns in input text efficiently.
How DFA and NFA help for Tokenization of “Regular Expression”.
Regular expressions (regex) are the universal tools for data pattern matching and processing text. In a widespread way, they are used in different programming languages, various text editors, and even software applications. Tokenization, the process that involves breaking down the text into smaller pieces called features using the tokens, plays a role in many language processing tasks, including word analysis, parsing, and data extraction. The idea of Deterministic Finite Automata (DFA) and Non-deterministic Finite Automata (NFA) is fundamental in computer science, among other things, because of defines the grammar rules of regular expressions (regex). This article details how DFA and NFA simplify the tokenization of regular expressions.