DATA WAREHOUSING AND DATA MINING Question paper


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1. (a) Explain data mining as a step in the process of knowledge discovery.
(b) Differentiate operational database systems and data warehousing.

2. Explain various data reduction techniques
.
3. Write the syntax for the following data mining primitives:
(a) The kind of knowledge to be mined.
(b) Measures of pattern interestingness.

4. (a) What is Concept description? Explain.
(b) What are the differences between concept description in large data bases and
OLAP?

5. Explain the Apriori algorithm with example.

6. Explain the following:
(a) Naive Bayesian classification
(b) Backpropagation and interpretability
© Linear and multiple regressions
(d) Classifier accuracy.

7. (a) Write k-Means and k-Medoids algorithms.
(b) Explain COBWEB model.

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.

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