Exam Details
Subject | web intelligent and algorithm | |
Paper | ||
Exam / Course | m.tech | |
Department | ||
Organization | Institute Of Aeronautical Engineering | |
Position | ||
Exam Date | July, 2017 | |
City, State | telangana, hyderabad |
Question Paper
Hall Ticket No Question Paper Code: BCS201
INSTITUTE OF AERONAUTICAL ENGINEERING
(Autonomous)
M.Tech II Semester End Examinations (Regular) July, 2017
Regulation: IARE-R16
WEB INTELLIGENT AND ALGORITHMS
(Computer Science and Engineering)
Time: 3 Hours Max Marks: 70
Answer ONE Question from each Unit
All Questions Carry Equal Marks
All parts of the question must be answered in one place only
UNIT I
1. Briefly explain the basic elements of intelligent applications.
What are the problems in page ranking algorithm and discuss the solution for these page ranking
problems.
2. Explain about the applications that are benefited from intelligent applications.
Briefly discuss the effect of teleportation between web pages.
UNIT II
3. Write the pseudocode for Predicting the rating of an item for a user.
Briefly discuss the key ideas behind content-based similarities.
4. Explain different categories of recommendation engines.
Write a brief note on concepts of distance and similarity in recommender systems.
UNIT III
5. Give the distinction between content-based and collaborative-based sources of metadata.
Explain different Categories of Tags based on how they are generated.
6. Illustrate basic strategy used to Combine the term vectors from a number of documents to form
a tag cloud.
Illustrate different steps involved in building a tag cloud.
UNIT IV
7. Explain different method commonly used for neighbourhood-based computation.
What is hybrid recommendation system? Explain Seven hybridization techniques.
8. What is constraint based recommendation system? discuss the applications of constraint based
recommendation system.
Justify the statement "Product Search Engines AreNot Good Product Recommendation Engines".
Page 1 of 2
UNIT V
9. What are decision trees? List the advantage of decision trees.
Briefly discuss about adwords problem with an example.
10. Differentiate between online and offline algorithms, discuss the examples for each algorithms.
Briefly discuss some of the challenges for the Semantic Web.
INSTITUTE OF AERONAUTICAL ENGINEERING
(Autonomous)
M.Tech II Semester End Examinations (Regular) July, 2017
Regulation: IARE-R16
WEB INTELLIGENT AND ALGORITHMS
(Computer Science and Engineering)
Time: 3 Hours Max Marks: 70
Answer ONE Question from each Unit
All Questions Carry Equal Marks
All parts of the question must be answered in one place only
UNIT I
1. Briefly explain the basic elements of intelligent applications.
What are the problems in page ranking algorithm and discuss the solution for these page ranking
problems.
2. Explain about the applications that are benefited from intelligent applications.
Briefly discuss the effect of teleportation between web pages.
UNIT II
3. Write the pseudocode for Predicting the rating of an item for a user.
Briefly discuss the key ideas behind content-based similarities.
4. Explain different categories of recommendation engines.
Write a brief note on concepts of distance and similarity in recommender systems.
UNIT III
5. Give the distinction between content-based and collaborative-based sources of metadata.
Explain different Categories of Tags based on how they are generated.
6. Illustrate basic strategy used to Combine the term vectors from a number of documents to form
a tag cloud.
Illustrate different steps involved in building a tag cloud.
UNIT IV
7. Explain different method commonly used for neighbourhood-based computation.
What is hybrid recommendation system? Explain Seven hybridization techniques.
8. What is constraint based recommendation system? discuss the applications of constraint based
recommendation system.
Justify the statement "Product Search Engines AreNot Good Product Recommendation Engines".
Page 1 of 2
UNIT V
9. What are decision trees? List the advantage of decision trees.
Briefly discuss about adwords problem with an example.
10. Differentiate between online and offline algorithms, discuss the examples for each algorithms.
Briefly discuss some of the challenges for the Semantic Web.
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