An Experimental Survey on Parsing with Neural and Finite Automata Networks

Parsing is the process of structuring a l inear depiction in accordance with a g iven grammar. The “linear depiction” may be a language sentence, a computer program, a weaving pattern, a sequence of biological strata, a part of music, actions in a ritual performance, in short any linear chain in which the preceding elements in some way confine the next element. Parsing with finite automata networks implies, in one way, the conversion of a regular expression into a minimal deterministic finite automaton, while parsing with neural networks involves parsing of a n atural language sentence. This research paper presents a twofold investigation on the various parsing techniques with (i) neural networks and (ii) finite automata networks. Consequently, the present research paper depicts a comprehensive comparison among a number of parsing techniques with neural networks followed by another in depth comparison flanked by a number of parsing techniques with finite automata networks.