Download AKTU B-Tech 6th Sem 2015-2016 NCS 066 Data Warehousing Data Mining Question Paper

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Paper ID : 110666

Roll No. NCS-066

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B. TECH.

Theory Examination (Semester-VI) 2015-16

DATA WAREHOUSING & DATA MINING

Time: 3 Hours

Max. Marks : 100

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Note: Attempt questions from all Sections as per directions.

Section-A

1. Attempt all parts of this section. Answer in brief. [2×10=20]

1. (a) Write some of the facts of the association rule mining.
2. (b) Briefly explain the concept of Frequent Item sets and Closed Item sets.

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3. (c) Briefly explain important approaches to build the data warehouse.
4. (d) Define KDD. Identify the phases in KDD process.
5. (e) Why data warehouse is maintained separately from database?

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Section-B

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2. Attempt any five questions from this section. (10×5=50)

1. (a) Draw the 3-tier data warehouse architecture. Explain ETL process.
2. (b) Explain the various types of OLAP servers. What are the steps for efficient processing of OLAP queries?
3. (c) Write the algorithm of decision tree induction. What are the methods that can be used for selecting the splitting criteria?
4. (d) Draw a box-and-whisker plot for the following data set :
   

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   126, 132, 138, 140, 141, 141, 142, 143, 144, 144, 144, 145, 146, 147, 148, 148, 149, 149, 150, 150, 150, 154, 155, 158, 158.
   Also find the outliers.
5. (e) Explain how query performance can be improved by cascading the operations.

Section-C

3. Attempt any two questions from this section. (15×2=30)

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1. Classify the tuple X= {Color = 'RED', Type = 'SUV' Origin = 'DOMESTIC'} using Naive Bayesian classification. Training data is given in the following table where class label is {STOLEN}.
   

   Color	Type	Origin	Stolen?
   Red	Sports	Domestic	Yes
   Red	Sports	Domestic	No
   Red	Sports	Domestic	Yes
   Yellow	Sports	Domestic	No
   Yellow	Sports	Imported	Yes
   Yellow	SUV	Imported	Yes
   Yellow	SUV	Domestic	No
   Red	SUV	Imported	No
   Red	Sports	Imported	Yes

2. (i) Describe the difference between the following approaches for the integration of data mining system with database or data warehouse systems: no coupling, loose coupling and semi tight coupling.
   (ii) Define and describe the basic similarities and differences among ROLAP, MOLAP and HOLAP.
3. Explain Chi-square test method. Show using chi-square test that gender and preferred reading are independent or not from given table. (Given are the observed counts).
   

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   	Male	Female	Total
   Fiction	250	200	450
   Non-Fiction	50	1000	1050
   Total	300	1200	1500

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