Publication Type : Conference Paper
Publisher : Springer
Source : Advances in Intelligent Informatics, 445-456, 2015. DOI: https://doi.org/10.1007/978-3-319-11218-3_40.
Url : https://link.springer.com/chapter/10.1007/978-3-319-11218-3_40
Campus : Amritapuri
School : School of Computing, School of Engineering
Center : AI (Artificial Intelligence) and Distributed Systems
Department : Computer Science
Verified : Yes
Year : 2015
Abstract : Relational model is one of the extensively used database models. However, with the contemporary technologies, high dimensional data which may be structured or unstructured are required to be analyzed for knowledge interpretation. One of the significant aspects of analysis is exploring the relationships existing between the attributes of large dimensional data. In relational model, the integrity constraints in accordance with the relationships are captured by functional dependencies. Processing of high dimensional data to understand all the functional dependencies is computationally expensive. More specifically, functional dependencies of the most prominent attributes will be of significant use and can reduce the search space of functional dependencies to be searched for. In this paper we propose a regression model to find the most prominent attributes of a given relation. Functional dependencies of these prominent attributes are discovered which are indicative and lead to faster results in decreased amount of time.
Cite this Research Publication : S. Harikumar, R. Reethima, "A Method to Induce Indicative Functional Dependencies for Relational Data Model," Advances in Intelligent Informatics, 445-456, 2015. DOI: https://doi.org/10.1007/978-3-319-11218-3_40.