Important RGPV Question
AL 504 (B) Natural Language Processing
V Sem, AIML
UNIT 1- Introduction
Q.1) Describe the role of regular expressions in NLP and provide examples of how they are used in language processing tasks?
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Q.2) Explain the key components of a Grammarians Language Model (LM) and how it functions in NLP?
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Q.3) Explore the challenges associated with detecting and Correcting Spelling Errors in natural language text.
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Q.4) List and explain the challenges of natural language processing.
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Q.5) Discuss in detail the basic regular expression patterns with examples.
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Q.6) Write and explain the minimum edit distance algorithm.
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UNIT 2- Word Level Analysis
Q.1) What is transformation-based tagging and how does it contribute to improving Part-of-Speech tagging accuracy?
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Q.2) Explain the principles of rule-based Part-of-Speech tagging.
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Q.3) What is smoothing in the context of N-gram models and why is it necessary? Provide example to show how smoothing works?
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Q.4) Explain how is perplexity calculated in evaluating N-grams.
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Q.5) Discuss in detail the Hidden Markov Model.
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UNIT 3- Syntactic Analysis
Q.1) How do CFGs capture the syntactic structure of sentences, and what are the key components of a CFG?
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Q.2) Explain the process of syntactic parsing.
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Q.3) What is the process involved in constructing treebanks, and how do they play a role in both the development and assessment of syntactic parsers?
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Q.4) What is ambiguity in parse tree? Explain with an example.
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Q.5) Explain in detail about dependency grammar.
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Q.6) Discuss in detail Probabilistic CYK.
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UNIT 4- Semantics and Pragmatics
Q.1) What is Word Sense Disambiguation in NLP?
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Q.2) Explain the concept of compositional semantics and how it contributes to understanding the meaning of complex expressions?
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Q.3) Explain the following word sense disambiguation methods: a) Supervised b) Dictionary c) Thesaurus
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UNIT 5- Application of NLP
Q.1) Explain how speech recognition works, and how NLP enhances this technology?
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Q.2) How does NLP make work processors smarter and more user-friendly?
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Q.3) How is NLP used in commercial applications to improve user experience and interaction?
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Q.4) Describe transfer model of machine translation. List out its three phases.
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Q.5) What are the commercial uses of NLP? Explain in detail.
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EXTRA QUESTIONS-
Q.1) Explain with an example how bigram probability is calculated.
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Q.2) Write short notes on following: a) Dictionary and Thesaurus b) First order logic c) Tokenization
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Q.3) Explain in detail about quantifiers with an example.
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Q.4) Write short notes on any two of the following: a) Finite-State Automata b) Laplace Smoothing c) Probabilistic context-free grammar d) Word sense
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— Best of Luck for Exam —
