NDLI: Materialized view construction using linear regression on attributes

Content Provider	IEEE Xplore Digital Library
Author	Ghosh, P. Sen, S. Chaki, N.
Copyright Year	2012
Description	Author affiliation: Department of Computer, Science & Engineering, University of Calcutta (Chaki, N.) \|\| A. K. Choudhury School of Information Technology University of Calcutta (Ghosh, P.; Sen, S.)
Abstract	Materialized view creation is an important aspect for large data centric applications. Materialized views create an abstraction over the actual database tables to the users. Users are not aware about the existence of these materialized views. However, these help in faster execution of query. Materialized views should contain the data that users are currently accessing, and possibly those that would be accessed in near future. Availability of the user-requested data in a materialized view indicates the efficacy of the materialized view creation process. A review of the existing research work reveals a gap in analyzing the inter-attribute affinity while creating the materialized views. This paper proposes a new methodology for materialized view creation by quantifying the association among the independent data attributes. This is done based on the usage of different attributes in the recently executed set of queries. Statistical analysis on existing query set help to predict the attributes likely to be used for future queries. The materialized views are generated accordingly.
Starting Page	214
Ending Page	219
File Size	891074
Page Count	6
File Format	PDF
ISBN	9781467318280
e-ISBN	9781467318273
DOI	10.1109/EAIT.2012.6407899
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-11-30
Publisher Place	India
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Measurement Quantitative Analysis Databases Linear Regression Materialized View Attribute Affinity Maintenance engineering Mathematical model Active appearance model Arrays Line fitting Equations
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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