JNTU B.Tech Examinations, Data Warehousing And Data Mining,
Data Warehousing And Data Mining
Time: 3 hours Max Marks: 80
Answer any FIVE Questions
All Questions carry equal marks
1. (a) Draw and explain the architecture of typical data mining system.
(b) Differentiate OLTP and OLAP. [8+8]
2. (a) Briefly discuss the data smoothing techniques.
(b) Explain about concept hierarchy generation for categorical data. [8+8]
3. (a) List and describe any four primitives for specifying a data mining task.
(b) Describe why concept hierarchies are useful in data mining. [8+8]
4. (a) How can we specify a data mining query for characterization with DMQL?
(b) Describe the transformation of a data mining query to a relational query.
5. Sequential patterns can be mined in methods similar to the mining of association
rules. Design an efficient algorithm to mine multilevel sequential patterns from
a transaction database. An example of such a pattern is the following “A customer
who buys a PC will buy Microsoft software within three months”, on which one
may drill down to find a more refined version of the patterns, such as “A customer
who buys a Pentium PC will buy Microsoft office within three months”. 
6. Discuss about Backpropagation classification. 
7. (a) What major advantages does DENCLUE have in comparison with other clustering algorithms?
(b) What advantages does STING offer over other clustering methods?
(c) Why wavelet transformation useful for clustering?
(d) Explain about outlier analysis. [3+3+3+7]
8. (a) Explain spatial data cube construction and spatial OLAP.
(b) Discuss about mining text databases. [8+8]