Information Retrieval - Unit Wise Questions

Questions Organized by Units
Unit 1: Introduction to IR and Web Search
23 Questions

1. How IR in web search is different from other IR systems? Discuss IR architecture with suitable diagram.(2+4)

6 marks
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1. How IR in web search is different from other IR systems? Discuss IR architecture with suitable example.

2+4 marks
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2. Assume that document Space is defined by four terms: Network, CSIT, Nepal, TU, and Graduate. 

And we have three documents containing the following terms:

Doc1: CSIT Nepal

Doc2: TU CSIT

Doc3: CSIT TU Nepal

If the Query is "CSIT Nepal", find top 2 document retrieved by Boolean space model.(6)

6 marks
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3. What is meant by stop word removal? Explain text normalization with suitable example.(1+5)

6 marks
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2. Assume that document space is defined by four terms: Network, CSIT, Nepal, TU and Graduate. And we have three documents containing the following terms:

Doc1: CSIT Nepal

Doc2: TU CSIT

Doc3: CSIT TU Nepal

If the query is "CSIT NEPAL", find top 2 documents retrieved by Boolean space model

6 marks
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3. What is meant by stop word removal? Explain text normalization with suitable example. 

1+5 marks
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4. Suppose that table below list all the documents retrieved by an algorithm. If total number of relevant documents is 6, calculate the value of recall, precision, and F-score.(6)


6 marks
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4. Suppose the table given below lists all the documents retrieved by an algorithm. If total number of relevant documents is 6, calculate the value of recall, precision, and F-score.


sn
Doc ID
relevant
1
D1no
2D2no
3D3yes
4D4no
5D5yes
6D6yes
7D7no
8D8no
9D9yes


6 marks
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5. Why query expansion is important? Discuss query expansion techniques with examples.(1+5)

6 marks
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6. Why Hits algorithm is used? Discuss its working with example.(2+4)

6 marks
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5. Why query expansion is important? Discuss query expansion techniques with examples.

1+5 marks
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7. How Bots are different from spiders? Describe simple and multithreded spidering algorithm.(1+5)

6 marks
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6. Why Hits algorithm is used? Discuss its working with example.

2+4 marks
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8. How text categorization is different from clustering? Explain nearest neighbor categorization algorithm.(1+5)

6 marks
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7. How Bots are different from spiders? Describe simple and multithreded spidering algorithm.

1+5 marks
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8. How text categorization is different from clustering? Explain nearest neighbor categorization algorithm.

1+5 marks
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9. Differentiate collaborative filtering from content based filtering? Discuss content based recommender system with its strengths and drawbacks.(2+4)

6 marks
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9. Differentiate collaborative filtering from content based filtering? Discuss content based recommender system with its strengths and drawbacks

2+4 marks
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10. Why TF-IDF weighting is important in information retrieval? Explain with suitable example.(6)

6 marks
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11. How information extraction differs from information retrieval? Discuss role of XML in information extraction.(6)

6 marks
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10. Why TF-IDF weighting is important in information retrieval? Explain with suitable example.

6 marks
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11. How information extraction differs from information retrieval? Discuss role of XML in information extraction.

6 marks
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12. Write short notes on:(3+3)

a) Latent Semantic Indexing

b) Spiders

6 marks
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Unit 2: Text properties, operations and preprocessing
0 Questions
Unit 3: Basic IR Models
0 Questions
Unit 4: Evaluation of IR
0 Questions
Unit 5: Query Operations and Languages
0 Questions
Unit 6: Web Search
0 Questions
Unit 7: Text Categorization
0 Questions
Unit 8: Text Clustering
0 Questions
Unit 9: Recommender System
0 Questions
Unit 10: Question Answering
0 Questions
Unit 11: Advanced IR Models
0 Questions