PRESENTATION: GROUP # 5 Roll No: 14,17,25,36,37 TOPIC: STATISTICAL PARSING AND HIDDEN MARKOV MODEL.

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Presentation transcript:

PRESENTATION: GROUP # 5 Roll No: 14,17,25,36,37 TOPIC: STATISTICAL PARSING AND HIDDEN MARKOV MODEL

PARSING  Parsing, or syntactic analysis, is a fundamental problem in the field of natural language processing.

STATISTICAL PARSING(1)  Statistical parsing is a group of parsing methods within natural language process.  The methods have in common that they associate grammar rules with a probability.  Statistical parsing essentially involves three steps: modeling, learning, and decoding.

CONT.  Modeling syntax trees is formalized as a probabilistic grammar.  Probabilistic grammars consist of a set of structural rules (tree fragments) that govern the composition of sentences, clauses, phrases, and words. Each rule, called an elementary tree, is assigned a probability.

STATISTICAL PARSING(2)  Most statistical parsing algorithms are based on a modified form of chart parsing.chart parsing  The modifications are necessary to support an extremely large number of grammatical rules and therefore search space, and essentially involve applying classical artificial intelligence algorithms to the traditionally exhaustive search.artificial intelligence