data mining
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Question Three |
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( Data Mining and Data Warehousing IT446 ) ( Assignment 2 D eadline : Saturday 03 / 11 / 2017 @ 14 :59 [Total Ma rk for this Assignment is [ 5 ] )
( Instructions: This Assignment must be submitted on Blackboard via the allocated folder. Email submission will not be accepted. You are advised to make your work clear and well-presented , marks may be reduced for poor presentation . You MUST show all your work . Late submission will result in ZERO marks being awarded. The work should be your own, copying from students or other resources will result in ZERO marks . Use Times New Roman font for all your answers . ) ( Student Details: Name: ### CRN : ### ID: ### )
College of Computing and Informatics
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( Learning Outcome(s): Student differentiate between different data warehouse model s and forms, Data forms , and OLTP and OLTP ) ( 1 Mark )Question One
Compare the following with the help of examples.
(a) Star schema and snowflake schema
(b) Data cleaning and data transformation
(c) Enterprise warehouse, data mart, and virtual warehouse
(d) OLAP and OLTP
( 1 Mark ) ( Learning Outcome(s): Student know three-tire data warehouse, data cube concept, understand data cube computation . )Question Two
a) Explain three tiers of data warehouse architecture.
b) Which methods are used for efficient computations of data cubes.
c) Which algorithm is most appropriate to compute closed iceberg cubes efficiently?
( 2 Marks ) ( Learning Outcome(s): Instructors: State the Learning Outcome(s) that match this question )Question Three
Consider the database containing transaction data as stated in the table below. Use Apriori algorithm to find frequent item sets where minimum support is 50%.
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Transactions |
Item Set |
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I1 |
A,B,C |
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I2 |
A,C |
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I3 |
A,D |
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I4 |
B,E,F |
( 1 Mark ) ( Learning Outcome(s): Instructors: State the Learning Outcome(s) that match this question )Question Four
Discuss candidate generation in Generalized Sequential Pattern (GSP) with the help of an example.