Download JNTUH MCA 5th Sem R13 2017 August 815BJ Information Retrieval Systems Question Paper

Download JNTUH (Jawaharlal nehru technological university) MCA (Master of Computer Applications) 5th Sem (Fifth Semester) Regulation-R13 2017 August 815BJ Information Retrieval Systems Previous Question Paper

R13

Code No: 815BJ

JAWAHARLAL NEHRU TECHNOLOGICAL UNIVERSITY HYDERABAD

MCA V Semester Examinations, August - 2017

INFORMATION RETRIEVAL SYSTEMS



Time: 3 Hours













Max. Marks: 60

Note: This question paper contains two parts A and B.

Part A is compulsory which carries 20 marks. Answer all questions in Part A. Part B
consists of 5 Units. Answer any one full question from each unit. Each question carries
8 marks and may have a, b, c as sub questions.



PART - A



















5 ? 4 Marks = 20

1.a) What is IR and provide an example for IR problem?







[4]

b) Describe the procedure for ,,pseudo relevance feedback.







[4]

c) Provide some basic XML concepts.











[4]

d) What is "Low rank approximations" in matrix decompositions?





[4]

e) What is the role of Web graphs in link analysis?









[4]



PART - B

















5 ? 8 Marks = 40


2.

How do we process a query using an inverted index and the basic Boolean retrieval
model? Explain with example.













[8]

OR

3.

Explain the following spelling correction strategies in brief.



a) K-gram indexes b) context sensitive.











[4+4]



4.

Write short notes on the following "parametric and zone indexes".



a) Weighted zone scoring

b) The optimal weighting.







[4+4]

OR

5.

Describe "Rocchio algorithm for relevance feedback".







[8]


6.a)

Compare text-centric and data-centric XML retrieval.

b)

What is "The 1/0 loss case" probability ranking principle?





[4+4]

OR

7.

Describe about "Query likelihood models in language models" for Information retrieval.

























[8]



8.

Write about the following models of extended support vector machines.



a) Soft margin classification b) Multi class SVMs.







[4+4]

OR

9.

Describe the following Hierarchical clustering methods.



a) Centroid clustering

b) Divisive Clustering.







[4+4]



10.

Explain the role of "Index size and clustering" in approximation of web search
comprehensiveness.















[8]

OR

11.

What is Web Crawling? Draw and explain the basic Web Crawler architecture.

[8]



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