Skip to Main content Skip to Navigation
Conference papers

A New Scale for Attribute Dependency in Large Database Systems

Abstract : Large, data centric applications are characterized by its different attributes. In modern day, a huge majority of the large data centric applications are based on relational model. The databases are collection of tables and every table consists of numbers of attributes. The data is accessed typically through SQL queries. The queries that are being executed could be analyzed for different types of optimizations. Analysis based on different attributes used in a set of query would guide the database administrators to enhance the speed of query execution. A better model in this context would help in predicting the nature of upcoming query set. An effective prediction model would guide in different applications of database, data warehouse, data mining etc. In this paper, a numeric scale has been proposed to enumerate the strength of associations between independent data attributes. The proposed scale is built based on some probabilistic analysis of the usage of the attributes in different queries. Thus this methodology aims to predict future usage of attributes based on the current usage.
Complete list of metadatas

Cited literature [13 references]  Display  Hide  Download

https://hal.inria.fr/hal-01551729
Contributor : Hal Ifip <>
Submitted on : Friday, June 30, 2017 - 2:43:20 PM
Last modification on : Tuesday, August 6, 2019 - 4:08:04 PM
Long-term archiving on: : Monday, January 22, 2018 - 8:54:05 PM

File

978-3-642-33260-9_23_Chapter.p...
Files produced by the author(s)

Licence


Distributed under a Creative Commons Attribution 4.0 International License

Identifiers

Citation

Soumya Sen, Anjan Dutta, Agostino Cortesi, Nabendu Chaki. A New Scale for Attribute Dependency in Large Database Systems. 11th International Conference on Computer Information Systems and Industrial Management (CISIM), Sep 2012, Venice, Italy. pp.266-277, ⟨10.1007/978-3-642-33260-9_23⟩. ⟨hal-01551729⟩

Share

Metrics

Record views

328

Files downloads

292