31-10-2012, 12:08 PM
Supplementary Examinations DATA WAREHOUSING AND DATA MINING question paper
DATA WAREHOUSING AND DATA MINING.pdf (Size: 184.44 KB / Downloads: 76)
1. (a) Explain data mining as a step in the process of knowledge discovery.
(b) Differentiate operational database systems and data warehousing. [8+8]
2. Explain various data reduction techniques. [16]
3. Write the syntax for the following data mining primitives:
(a) The kind of knowledge to be mined.
(b) Measures of pattern interestingness. [16]
4. (a) What is Concept description? Explain.
(b) What are the differences between concept description in large data bases and
OLAP? [8+8]
5. Explain the Apriori algorithm with example. [16]
6. Explain the following:
(a) Naive Bayesian classification
(b) Backpropagation and interpretability
© Linear and multiple regressions
(d) Classifier accuracy. [4+4+4+4]
7. (a) Write k-Means and k-Medoids algorithms.
(b) Explain COBWEB model. [8+8]
8. (a) Explain the classification and prediction analysis of multimedia data.
(b) What are basic measures for text retrieval? What methods are there for
information retrieval?
© What is meant by ‘authoritative’Web pages? Explain about mining theWeb’s
link structures to identify authoritative web page.