Anna University Questions - CS9040 Language Technology April May 2014, Computer Science and Engineering (CSE), Seventh Semester, Regulation 2008
Exam
|
B.E/B.Tech. (Full
Time) DEGREE END SEMESTER EXAMINATIONS
|
Academic
Year
|
April May 2014
|
Subject
Code
|
CS9040 |
Subject
Name
|
Language Technology |
Branch
|
Computer Science and Engineering
|
Semester
|
Seventh Semester
|
Regulation
|
2008
|
B.E
/ B.Tech. (Full Time) DEGREE END SEMESTER EXAMINATIONS, APRIL / MAY 2014
Computer Science
and Engineering
Seventh Semester
CS9040
LANGUAGE TECHNOLOGY
(Regulations 2008)
Time : 3 Hours Answer A L L Questions Max. Marks 100
PART-A
(10 x 2 = 20 Marks)
1. What is the difference between
Natural Language Processing and Language Technology? Explain.
2. How is probability used in syntax
analysis?
3. How is Information Extraction
different from Information retrieval?
4. Compare and Contrast Document
categorization and Document Clustering.
5. Differentiate between Generative
and Discriminative Models.
6. What is Word Sense Disambiguation?
Illustrate using examples.
7. How is Information Retrieval
evaluated?
8. How is machine translation
evaluated?
9. Outline Grice's Maxims regarding
Discourse?
10. Discuss one application where you
need speech, text and image.
Part-B
(5* 16 = 80 Marks)
11. Imagine that you are a personal
assistant to the Managing Director of a Multinational Company. You are required
to handle all documents for the Company. In case you are replaced by
semi-automatic system with Language Technology skills, list out and explain
with a block diagram all the skills required and the corresponding Language
Technology issues. (16)
12. (a) (i)Explain in detail two level
Morphological Analysis used for natural language. Discuss the use of this
technique for an Indian Language of your choice. Clearly explain the
morphological rules used. (10)
(ii) Describe a typical
Morphographemic Transducer with an example. (6)
OR
12 (b) (i) Explain the Earley
algorithm in detail. (3)
ii) Simulate the Earley algorithm for
the grammar given below: (7)
S-> NP VP NP
-> Ram
S -> VP NP N
-> spoon
NP->Det N N->payasam
NP-> NP PP V
-> ate
VP-> V NP N
-> dish
VP-> V NP NP P
-> with
VP-> VP PP P
-> in
PP-> P NP Det
-> the
Det->a
The sentence is "Ram ate the
payasam in the dish with a spoon" (7)
(iii) Give a detailed account of
Thematic roles and Case Frames with suitable examples from English and an
Indian Language of your choice. (6)
13.(a) (i) Compare and contrast
Information Retrieval and Web Search. (4)
(ii) Explain the Vector Space Model
used for Information Retrieval. (6)
(iii) Explain the PageRank algorithm
used by Google. (6)
OR
13 (b) (i) Discuss the various steps
in a typical Information Extraction System. (8)
(ii) Explain how relations are
extracted from plain text using the Snowball system. (8)
14 (a) (i) Explain how Naive Bayes
Classifier is used to classify text. (8)
(ii) Explain how multilingualism and
multimodality can be used to enhance a web search engine. Discuss the methods
used for the integration (8)
OR
14(b) (i) Discuss the SVM algorithm in
detail. (6)
(ii) Explain how SVM algorithm is used
for document classification explaining the various issues. (6)
(iii) Write a short note on speech
coding. (4)
15 (a) (i) Explain the different
approaches to machine translation. (4)
(ii) We need to translate an Indian
Language of your choice to English. Discuss the various stages of statistical
machine translation required for the task. (8)
(iii) Explain how speech acts are
generally used to describe illocutionary acts. (4)
OR
15 (b) Write Short Notes on any two of the following: (2X8)
(i) Natural Language Generation system
(ii) Question Answering System
(iii) Discourse Processing
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