A New Scale for Attribute Dependency in Large Database Systems

  • Soumya Sen
  • Anjan Dutta
  • Agostino Cortesi
  • Nabendu Chaki
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7564)


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.


Materialized view Query Processing Attribute dependency Numeric scale Query Optimization 


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Copyright information

© IFIP International Federation for Information Processing 2012

Authors and Affiliations

  • Soumya Sen
    • 1
  • Anjan Dutta
    • 1
  • Agostino Cortesi
    • 1
  • Nabendu Chaki
    • 2
  1. 1.University of CalcuttaKolkataIndia
  2. 2.Universita Ca FoscariVeniceItaly

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