TYMCA (Engg. Faculty) (Semester - V),2014 Question Paper,University Of Pune Question Paper,ADVANCED DATABASES

University Of Pune Question Paper
TYMCA (Engg. Faculty)
ADVANCED DATABASES
(Semester - V) (2008 Pattern) (710903)
MAY 2013 EXAMINATIONS
Time: 3 Hours] [Max. Marks : 70]
Instructions to the candidates:
1) Answers to the two sections should be written in separate books.
2) Neat diagrams must be drawn wherever necessary.
3) Assume Suitable data if necessary.
SECTION I
Q1) a) With suitable diagrams explain the steps in query processing. [5]
b) Explain the external sort merge algorithm with suitable example. [6]
OR
Q2) a) What are the measures of query cost? [5]
b) Explain the different ways of executing pipelines. [6]
Q3) a) Explain Transaction Server Process Structure. [6]
b) What are the implementation issues of distributed systems. [6]
OR
Q4) a) Explain Speed up & Scale up. [6]
 b) Explain centralized and client server database architecture [6]
Q5) a) Explain object identity and reference type? [6]
b) Why OODBMS is required Differentiate between DBMS, RDBMS and
OODBMS.
[6]
OR
Q6) a) Explain Array and Multiset in SQL with example. [6]
b) Explain persistent C++ system. [6]
SECTION II
Q7) a) While analyzing the data, it was found that many tuples have no recorded values
for several attributes. How this problem of missing values can be solved?
[6]
b) Explain snowflake schema for multidimensional database. [6]
OR
Q8) a) Explain in brief OLAP. What are the possible operations on cube? [6]
b) Explain star schema for multidimensional database. [6]
[4366]-503 Page 2 of 2
Q9) a) Form clusters using clustering K-Means algorithm. Use appropriate distance
formula.
RID       Age               Years of Service
1           30                           5
2           50                         25
3           50                         15
4           25                           5
5           30                         10
6           55                         25
 [8]
b) Explain outlier analysis [4]
OR
Q10) a) Find frequently occurred item using apriori algorithm.
TID     ITEM
100       1,3,4
200       2,3,5,
300      ,2,3,5
400          2,5
 [8]
b) Explain descriptive & predictive data mining. [4]
Q11) a) Describe the ranking using TF-IDF. [8]
b) Define the following terms.
1) Hub 2) Authority 3) Web crawler
 [3]
OR
Q12) a) Describe the popularity ranking. [8]
b) Define the following terms-
1) Ontology 2) Search engine spamming 3) False positive
 [3]

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