Year: 2010
Type: article
Abstract: Most of the existing data mining algorithms handle databases consisting of single table to find association rules an large databases.Few algorithms work on multiple tables having fuzzy data with taxonomic structures.This paper proposes 'Multi level Fuzzy rules for ER Models' algorithm.The study focuses on the issue of mining association rules in databases having multiple levels containing fuzzy data with taxonomy and tables to be designed using Entity-Relationship (ER) Models.The study aims to incorporate the previous developed algorithms Extended Apriori and Apriori star to a new algorithm.The study will help in standardizing algorithms for finding appropriate results from database tables containing data with fuzzy taxonomic structures.
Authors: Praveen Arora, R. K. Chauhan, Ashwani Kush
Institution: Kurukshetra University
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W2009587723