Question 1
(a)
Define: Structured data, Boolean query, Inverted index
3 Marks
(b)
What is Information Retrieval? Explain the process of IR.
4 Marks
(c)
Explain text classification using k-nearest neighbor classification approach.
7 Marks
Gujarat Technological UniversityWinter 2025 Examination
GTU 3170718 Information Retrieval (IR) Winter 2025 Paper Solution & PDF
B.E. · Computer Engineering · Semester 7 · Subject Code: 3170718
Total Marks70 MarksExternal theory exam
Passing Marks23 Marks33% minimum cutoff
Exam Duration2.5 Hours10:30 AM – 1:00 PM
Paper Structure5 QuestionsWith internal OR choices
Question 2
(a)
What is token? Which are the different issues in tokenization?
3 Marks
(b)
How to compute tf-idf weight for a specific term and document? Explain.
4 Marks
(c)
Explain:
i)Blocked sort based indexing
ii)Dynamic indexing
7 Marks
OR OPTION
(c)
Explain:
i)Cosine measure
ii)Document length normalization
7 Marks
Question 3
(a)
What is F-measure? Why F-measure is required?
3 Marks
(b)
What is precision and recall? An IR system returns 23 relevant documents, and 17 nonrelevant documents. There are a total of 35 relevant documents in the collection. What is the precision and recall of the system on this search?
4 Marks
(c)
Discuss about user relevance feedback. Illustrate the cases where use of only relevance feedback is not enough?
7 Marks
OR OPTION
(a)
Identify the requirement of spam filters.
3 Marks
(b)
Illustrate boosting technique with any one algorithm.
4 Marks
(c)
Explain kappa statistic. How is it interpreted? Consider agreement details of two judges on document relevance. Compute kappa statistic for the given details: Judge Relevant Non-Relevant Judge 1 Relevant 250 20 Non-relevant 15 45
7 Marks
Question 4
(a)
What is text classification? List out examples of text classification in the context of information retrieval.
3 Marks
(b)
What is hierarchical agglomerative clustering? Explain.
4 Marks
(c)
Discuss:
i)N-gram index
ii)Zipf’s law
7 Marks
OR OPTION
(a)
Which are the limitations of k-means clustering?
3 Marks
(b)
Explain clustering based on Gaussian mixture model.
4 Marks
(c)
Demonstrate SVM classifier. Explain any three kernel functions.
7 Marks
Question 5
(a)
What do you mean by text summarization? Mention its types.
3 Marks
(b)
Explain: Page rank, HITS, XML retrieval, Semantic web
4 Marks
(c)
Illustrate cross language information retrieval and the approaches used for it.
7 Marks
OR OPTION
(a)
Write short note on question answering.
3 Marks
(b)
Discuss web crawler architecture.
4 Marks
(c)
Which are the basic tasks in topic detection and tracking? What is story in this context?
7 Marks
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About this Examination Paper & Attribution
Official Gujarat Technological University (GTU) examination paper and step-by-step solutions for Information Retrieval (IR) (Winter 2025, B.E. · Computer Engineering, Sem 7). Features complete 70-mark regular & remedial examination pattern, official marking distribution across all 5 questions, and direct 1-click official PDF download.
Transcribed for student exam preparation from Gujarat Technological University official examination archives. Questions, syllabus guidelines, and curriculum marking schemes remain the intellectual property of Gujarat Technological University.