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JNTU MCA 2019 INFORMATION RETRIEVAL SYSTEMS Previous Question Paper (April/May - 2019 - R15)

MCA | 2019 | V | R15 | April/May - 2019

Answer PaperPaper Code: 825ADMaximum Marks: 75Time: 3 Hours

Part A is compulsory. Answer all questions in Part A. Part B consists of 5 Units. Answer any one full question from each unit.

Part A

125 marks
a

Explain with an example the concept of Biword Indexes.

5 marks

Answer

A Biword Index is a technique used to handle phrase queries by indexing pairs of consecutive terms as a single token. Instead of storing individual words, the system stores adjacent word pairs, such as "data mining" or "information retrieval," in the dictionary. This allows for efficient retrieval of multi-word phrases without complex post-processing. For example, the sentence "The quick brown fox" would be indexed as the biwords "the quick," "quick brown," and "brown fox."

b

What is Inverse document frequency?

5 marks

Answer

Inverse Document Frequency (IDF) measures how much information a word provides, specifically whether it is common or rare across all documents in a collection. It is calculated as the logarithm of the total number of documents divided by the number of documents containing the term. A high IDF value indicates a rare, highly informative term, while a low IDF value indicates a common term that carries less discriminative power for retrieval.

IDF(t) = log(N / df(t))

Where N is the total number of documents and df(t) is the number of documents containing term t.

c

What is Probabilistic Information Retrieval?

5 marks

Answer

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d

What is Hierarchical Clustering?

5 marks

Answer

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e

Write a brief note on The Web Graph.

5 marks

Answer

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Part B

2

Explain in detail about Distributed indexing.

10 marks

Answer

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OR
310 marks
a

Write a detailed note on Dynamic Indexing.

5 marks

Answer

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b

Explain in detail about Dictionary compression.

5 marks

Answer

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4

Explain in detail about following Components of an information retrieval system: a) Relevance feedback b) Query-term proximity.

10 marks

Answer

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OR
510 marks
a

Explain in detail about the Evaluation of Unranked Retrieval Sets.

5 marks

Answer

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b

Explain how Assessing relevance is done for evaluating a system.

5 marks

Answer

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6

Write a detailed note on vector space model for XML retrieval.

10 marks

Answer

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OR
710 marks
a

Explain in detail about the Text Classification problem.

5 marks

Answer

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b

Write a detailed note on Rocchio classification.

5 marks

Answer

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810 marks
a

Explain various components used in Evaluation of clustering.

5 marks

Answer

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b

Explain in detail about Single-link and complete-link clustering.

5 marks

Answer

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OR
910 marks
a

Write a detailed note on Low-rank approximations in Matrix Decompositions.

5 marks

Answer

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b

Explain in detail about Group-average agglomerative clustering.

5 marks

Answer

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10

What is a Web Crawler? Explain its architecture with a neat diagram.

10 marks

Answer

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OR
1110 marks
a

Write a detailed note on Connectivity servers required by Web Search Engines.

5 marks

Answer

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b

Write a detailed note on Hubs and Authorities.

5 marks

Answer

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