Download AKTU B-Tech 8th Sem 2016-17 NIT080 Natural Language Processing Question Paper

Download AKTU (Dr. A.P.J. Abdul Kalam Technical University (AKTU), formerly Uttar Pradesh Technical University (UPTU) B-Tech 8th Semester (Eight Semester) 2016-17 NIT080 Natural Language Processing Question Paper

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B.TECH.
THEORY EXAMINATION (SEM?VIII) 2016-17
NATURAL LANGUAGE PROCESSING
M ax. Marks .' I 00
Note : Be precise in your answer. In case ofnumerical problem assume data wherever not provided.
SECTION-A
1 Explain the following: (10X2=20)
a) Issues and problems in NLP
b) Lexicon
0) Advantages of speech understanding system
d) Left associative grammars
e) Best first parsing
f) Scope of ambiguity in natural languages
g) Differentiate syntax and semantics
h) Probabilistic context-free grammars
i) Stochastic Part?of?Speech tagging
j) Elements of a language
SECTION-B
2 Attempt any ?ve of the following: (10X5=50)
a) How the natural language processing systems are evaluated? Explain.
b) What are the differences between the natural language processing and natural language
understanding?
0) What is the need of NLP system? Why is it difficult to process the natural languages?
d) What are the issues in parsing? Describe various techniques used for parsing with
suitable example.
e) What are the different levels in language analysis? Explain with examples.
f) Explain in detail about the organization of NLP systems.
g) What are the different ways in which a speech dialogue system can reduce the number
of errors made because of incorrect speech recognition?
h) How the man?machine interface is designed using NLP techniques? Explain with
example.
SECTION-C
Attempt any two of the following: (15X2=30)
3. How the knowledge is represented using semantic networks? Also explain how information is
deduced from semantic networks.
4. Give an example of an NLP system or approach that only knows about individual words (not
about their context). Explain what knowledge of words it needs and given an overview of how
it works. Give examples to illustrate your explanation.
5. Write an algorithm for converting an arbitrary context-free grammar into Chomsky normal
form. Explain it with suitable examples.
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