Gujarat Technological UniversitySummer 2023 examination

GTU 3160714 Data Mining Summer 2023 Question Paper & PDF

B.E. · Computer Engineering · Semester 6 · Subject code 3160714
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Total
70 marks
To pass
23 marks (33%)
Duration
2.5 Hours 10:30 AM – 1:00 PM
Questions
5 with internal choice
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7 of 25 questions on this paper were also asked in other years. 1 more is a type of question GTU sets again with new data. Each is marked below with the years it appeared.See all 27 repeated 3160714 questions, most asked first

Q.1

14 Marks
(a)
3 marks
What is market basket analysis? Precisely explain the meaning of the
following association rule:
computer → antivirus_software [support = 60%, confidence = 60%]
(b)
4 marksAsked in 4 of 7 papers

In real-world data, tuples with missing values for some attributes are a common occurrence. List and describe various methods for handling this problem.

Also asked in Summer 2025 Q2b, Winter 2024 Q2a, Summer 2024 Q2c

(c)
7 marksAsked in 7 of 7 papers

With the help of a suitable diagram, describe the steps involved in data mining when viewed as a process of knowledge discovery.

Also asked in Summer 2026 Q1c, Winter 2025 Q2c, Summer 2025 Q1b, Winter 2024 Q1c, Summer 2024 Q1b, Winter 2023 Q1c

Q.2

14 Marks
(a)
3 marks

Give a short example to show that items in a strong association rule are not always interesting.

(b)
4 marks

Briefly describe how partitioning technique may improve the efficiency of Apriori algorithm.

(c)
7 marks

Discuss how frequent itemsets can be generated using FP-Growth algorithm with the help of the following transactions. Let minimum support threshold is 2. Transaction ID Item IDs T1 I1, I2, I5 T2 I2, I4 T3 I2, I3 T4 I1, I2, I4 T5 I1, I3 T6 I2, I3 T7 I1, I3 T8 I1, I2, I3, I5 T9 I1, I2, I3

(c)
7 marksSame type asked in 3 of 7 papers

A database has the following six transactions. Transaction ID Items T1 HotDogs, Buns, Ketchup T2 Chips, Coke T3 Coke, Chips, HotDogs T4 Ketchup, Chips T5 Buns, HotDogs T6 HotDogs, Chips, Coke Find all frequent itemsets and also generate the strong association rules using Apriori algorithm. Let minimum support threshold is 33.34% and minimum confidence threshold is 60%.

Also asked in Winter 2024 Q2c, Winter 2023 Q2c OR

Q.3

14 Marks
(a)
3 marks
Describe any three primitives for specifying a data mining task.
(b)
4 marks

The following table shows the midterm and final exam grades obtained by students in a database course. x (Midterm exam) y (Final exam) 72 84 50 63 81 77 74 78 94 90 86 75 59 49 83 79 65 77 33 52 88 74 81 90 Use the method of least squares to find an equation for the prediction of a student’s final exam grade based on the student’s midterm grade in the course. Predict the final exam grade of a student who received 86 grade in the midterm exam.

(c)
7 marks

What is noise? Describe the possible reasons for noisy data. Explain the different techniques to remove the noise from data.

(a)
3 marksAsked in 4 of 7 papers

Discuss outlier analysis as a data mining functionality with the help of an example.

Also asked in Winter 2025 Q5a, Summer 2025 Q5b, Winter 2024 Q4b OR

(b)
4 marks

Explain how classification rules are extracted from a decision tree with the help of an example.

(c)
7 marks

Explain in detail - min-max normalization method. Use this method to normalize the following group of data by setting min = 0 and max = 1. 200, 400, 600, 1000

Q.4

14 Marks
(a)
3 marksAsked in 3 of 7 papers
Differentiate classification and clustering.

Also asked in Winter 2025 Q5b, Winter 2024 Q4a

(b)
4 marks
Discuss data matrix and dissimilarity matrix with respect to clustering.
(c)
7 marks

Apply ID3 classification algorithm on the following data and construct a decision tree. Show all the stepwise calculations clearly. age income student credit_rating Class: buys_computer youth high no fair no youth high no excellent no middle_aged high no fair yes senior medium no fair yes senior low yes fair yes senior low yes excellent no middle_aged low yes excellent yes youth medium no fair no youth low yes fair yes senior medium yes fair yes youth medium yes excellent yes middle_aged medium no excellent yes middle_aged high yes fair yes senior medium no excellent no

(a)
3 marksAsked in 2 of 7 papers

Discuss cross-validation method for evaluating the accuracy of a classifier.

Also asked in Winter 2025 Q2a

(b)
4 marksAsked in 4 of 7 papers

How k-means clustering method differs from k-medoids clustering method? Discuss major drawbacks of k-means clustering method.

Also asked in Summer 2026 Q5b, Summer 2024 Q5b OR, Winter 2023 Q5a

(c)
7 marks

Predict class label of the tuple X = (age = youth, income = medium, student = yes, credit_rating = fair) with the help of Naive Bayesian classification method and the following data. Show all the stepwise calculations clearly. age income student credit_rating Class: buys_computer youth high no fair no youth high no excellent no middle_aged high no fair yes senior medium no fair yes senior low yes fair yes senior low yes excellent no middle_aged low yes excellent yes youth medium no fair no youth low yes fair yes senior medium yes fair yes youth medium yes excellent yes middle_aged medium no excellent yes middle_aged high yes fair yes senior medium no excellent no

Q.5

14 Marks
(a)
3 marks
Discuss web structure mining.
(b)
4 marks
Discuss multimedia mining.
(c)
7 marks

Suppose that the data mining task is to cluster the following eight points (with (x, y) representing location) into three clusters: A1(2, 10), A2(2,

5), A3(8,
4), B1(5,
8), B2(7,
5), B3(6,
4), C1(1,
2), C2(4,
9)The distance function is Euclidean distance. Suppose initially we assign A1, B1, and C1 as the center of each cluster, respectively. With the help of k-means algorithm calculate,
i)The three cluster centers after the first round execution
ii)The final three clusters
(a)
3 marks
Discuss agglomerative hierarchical clustering method in brief.
(b)
4 marksAsked in 4 of 7 papers
Explain the any four typical requirements of clustering in data mining.

Also asked in Summer 2025 Q5a, Summer 2024 Q5c OR, Winter 2023 Q4c OR

(c)
7 marks
What is web mining? Explain web usage mining in detail.

More Data Mining papers

Questions repeat across sessions. Working through two or three papers shows you which topics GTU asks most.

Summer 202670 marks · 5 questions
Winter 202570 marks · 5 questions
Summer 202570 marks · 5 questions
Winter 202470 marks · 5 questions

Other Semester 6 subjects

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116AG01
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2160701
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2160704
Theory of Computation
2160707
Advanced Java

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About this paper

Official Gujarat Technological University (GTU) examination paper for Data Mining (Summer 2023, B.E. · Computer Engineering, Sem 6). 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.

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