STUPIDSID
Solve any one question from Q.1(a,b) &Q.2(a,b)
1(a)
Show how single link clusters may be derived from the dissimilarity coefficient by thresholding it.
5 M
1(b)
You are developing a text processing system for use in an automatic retrieval System. Explain the following parts:
Removal of high frequency words.
Suffix stripping.
Detecting equivalent stems.
Removal of high frequency words.
Suffix stripping.
Detecting equivalent stems.
5 M
2(a)
Find the similarity of following query with D1, D2, D3, Using vector model.
| Query | keywords | |
| q | ant, dog | |
| document | Text | Terms |
| D1 | ant ant bee | ant bee |
| D2 | dog bee dog hog dog ant dog | ant bee dog hog |
| D3 | cat gnu dog eel fox | cat dog eel fox gnu |
6 M
2(b)
Write a short note on user oriented measures to evaluate the performance of the system.
4 M
Solve any one question from Q.3(a,b) &Q.4
3(a)
Write a note on "Ontology based information sharing".
5 M
3(b)
Explain the concept of hash addressing.
5 M
4(a)
Consider a reference collection and its set of example information request. If q is the information request and a set Rq = (d3, d5, d9, d25, d39, d44, d50, d70, d80, d120). Now consider new retrieval algorithmhas been designed and has been evaluated for information request q returns, ranking of the documents in the answer set as.
The documents that are relevant to the query q are underlined. Calculated precision and recall for the documents that are relevant to the query q.
| 1. | d120 |
| 2. | d84 |
| 3. | d50 |
| 4. | d6 |
| 5. | d8 |
| 6. | d9 |
| 7. | d58 |
| 8. | d129 |
| 9. | d143 |
| 10. | d25 |
| 11. | d38 |
| 12. | d48 |
| 13. | d230 |
| 14. | d113 |
| 15. | d3 |
The documents that are relevant to the query q are underlined. Calculated precision and recall for the documents that are relevant to the query q.
10 M
Solve any one question from Q.5(a,b) & Q.6(a,b)
5(a)
Describe the architecture of distributed IR.
8 M
5(b)
What do you understand by multimedia query language? Explain various query predicates.
8 M
6(a)
What are the issues in distributed IR computing? Write the techniques used to address these issues.
8 M
6(b)
Write a note on MULTOS.
8 M
Solve any one question from Q.7(a,b) &Q.8(a,b)
7(a)
Write a short note on web data mining.
8 M
7(b)
What is page ranking? Calculate page rank of following web pages. Assume damping factor 7.0.
!mage
!mage
10 M
8(a)
Explain centralized and distributed architecture of a search engine.
10 M
8(b)
What is web crawling? Explain the techniques used by web crawlers to crawl the web
8 M
Solve any one question from Q.9(a,b) Q.10(a,b)
9(a)
What is content based recommendation?
8 M
9(b)
Explain semantic web in details.
8 M
10(a)
Define Recommender system? Explain in brief collaborative filtering
8 M
10(b)
Discuss trends and research issues involved in web
8 M
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