Download PTU M.Tech IT 2nd Semester 72888 NATURAL LANGUAGE PROCESSING Question Paper

Download PTU. I.K. Gujral Punjab Technical University (IKGPTU) M.Tech IT 2nd Semester 72888 NATURAL LANGUAGE PROCESSING Question Paper.

1 | M-72888 (S9)-2086
Roll No. Total No. of Pages : 02
Total No. of Questions : 08
M.Tech.(IT) E-1(2015 & Onwards)/(CSE Engg.)EL-I (2015 to 2017)
(Sem.?2)
NATURAL LANGUAGE PROCESSING
Subject Code : MTCS-204
M.Code : 72888
Time : 3 Hrs. Max. Marks : 100

INSTRUCTIONS TO CANDIDATES :
1. Attempt any FIVE questions out of EIGHT questions.
2. Each question carries TWENTY marks.

1. What are the components of a natural language processing system? Explain the steps
involved in the process of natural language processing with suitable examples.
2. Write a detailed note on the computational structure of morphological paradigms.
3. Describe the following with suitable example :
a. Reference resolution.
b. Elements of a language.
4. How is the Naive Bayes machine learning algorithm applied as a method for learning the
word senses for an ambiguous word? Give the formula and explain how the necessary
parameters can be trained.
5. Describe how Hidden Markov Models are deployed for speech recognition.
6. What is the idea behind statistical machine translation? Explain the various statistical
approaches to translation with their benefits and shortcomings.


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1 | M-72888 (S9)-2086
Roll No. Total No. of Pages : 02
Total No. of Questions : 08
M.Tech.(IT) E-1(2015 & Onwards)/(CSE Engg.)EL-I (2015 to 2017)
(Sem.?2)
NATURAL LANGUAGE PROCESSING
Subject Code : MTCS-204
M.Code : 72888
Time : 3 Hrs. Max. Marks : 100

INSTRUCTIONS TO CANDIDATES :
1. Attempt any FIVE questions out of EIGHT questions.
2. Each question carries TWENTY marks.

1. What are the components of a natural language processing system? Explain the steps
involved in the process of natural language processing with suitable examples.
2. Write a detailed note on the computational structure of morphological paradigms.
3. Describe the following with suitable example :
a. Reference resolution.
b. Elements of a language.
4. How is the Naive Bayes machine learning algorithm applied as a method for learning the
word senses for an ambiguous word? Give the formula and explain how the necessary
parameters can be trained.
5. Describe how Hidden Markov Models are deployed for speech recognition.
6. What is the idea behind statistical machine translation? Explain the various statistical
approaches to translation with their benefits and shortcomings.


2 | M-72888 (S9)-2086
7. List and define three parsing strategies. Given the grammar and lexicon below, show the
final chart for the sentence ?Find the men in suits?. after applying the bottom-up chart
parser.
S ? VP
VP ? Verb NP
NP ? NP PP
NP ? Det Noun
PP ? Prep Noun
Det ? the
Verb ? Find
Prep ? in
Noun ? men | suits
8. a. Discuss lexemes and word forms.
b. In English morphology, ?y? maps to ?ie? when preceded by a consonant and followed
by the affix ?s? Give a finite state transducer that implements this spelling rule,
explaining the notation that is used. The transducer should accept the following
pairings: party/party, parties/party^s, partying/party^ing. It should reject:
partys/party^s, toies/toy^s.




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page of Answer Sheet will lead to UMC against the Student.
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