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2003 Course Advanced Databases (Elective I)

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Total No. of Questions :12] [Total No. of Pages : 3 P1377 [3764]-416 B.E. (Computer Engineering) ADVANCED DATABASES (2003 Course) (410445) (Elective - I) Time :3 Hours] [Max. Marks : 100 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) Figures to the right indicate full marks. 4) Assume suitable data, if necessary. SECTION - I Q1) a) b) Explain any two partitioning techniques with respect to parallel database system in detail. [8] Explain the following with respect to parallel database system. i) Intraoperation and interoperation parallelism. ii) [8] Fragment - and - Replicate join. OR Q2) a) b) Explain interquery and intraquery parallelism. Explain the following with respect to parallel database system. i) Range Partitioning sort. ii) Q3) a) [8] [8] Skew. Describe and compare homogenous and heterogenous databases with respect to distributed databases. [4] b) Explain deadlock handling with respect to distributed databases. [6] c) What is the major disadvantage of the Two phase commit protocol in distributed databases? How it is overcome in Three phase commit [8] protocol? OR P.T.O. Q4) a) What are the different approaches to store a relation in the distributed database.Explain them in brief. [4] b) Explain any two locking protocols with respect to distributed databases. [6] c) Discuss the different system failures modes in distributed system. [8] Explain in detail the XML document. [8] Write short notes on : [8] Q5) a) b) i) ii) SOAP. Client Server architecture. OR Q6) a) b) Explain in detail 3 Tier architecture. [8] Write short notes on : [8] i) ii) Domain specific DTD. Querying XML data. SECTION - II Q7) a) b) What is a data cube? Explain any two operations on data cubes. [8] Discuss the different ways of handling missing values in data cleaning.[8] OR Q8) a) What is meant by OLAP? Explain in brief. [6] b) Discuss the different data smoothing techniques. [8] c) What is meant by ETL Tool? [2] What are Bayesian classifiers? [2] b) State and explain K-means algorithm for clustering. [8] c) What is the difference between descriptive and predictive data mining? [2] d) Explain outlier analysis. Q9) a) [4] OR Q10)a) Explain the Market Basket analysis in brief. [5] b) What is a decision tree? How are decision trees used for classification? Why are decision tree classifiers so popular? [8] c) Explain Text mining in brief. [3764]-416 2 [3] Q11) a) b) Explain in the detail the measuring of the retrieval effectiveness. Explain the following terms : i) [10] Term frequency. ii) [8] Relevance. iii) Proximity. iv) Concept based querying. v) Stop words OR Q12) a) Explain in detail popularity ranking. [8] b) Explain the following terms. [10] i) Web crawlers. ii) Page Rank. iii) Full text retrieval. iv) Inverse document frequency. v) Homonyms. #### [3764]-416 3

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