Effective rule induction using incremental approach for a dynamic information system

Author

Tripathy, B.K. ; Kumaran, K. ; Sumaithri, M. ; Swathi, T.

Author_Institution

SCSE, VIT Univ., Vellore, India

Volume

3

fYear

2011

fDate

8-10 April 2011

Firstpage

308

Lastpage

312

Abstract

In the present day scenario, there are large volumes of data available in several fields, which we can make use of effectively, for decision making. This can be achieved by inducing rules through various rule induction approaches that are available. In this paper, we proposed a rule induction algorithm, ELEM, which is an enhanced version of one of the existing rule induction algorithms, LEM1 (3). This is made effective by reducing the database scans required to generate the rules. Also, it provides an incremental approach which makes use of ELEM and deals with any kind of data changes in a dynamic information system.

Keywords

decision making; learning (artificial intelligence); very large databases; ELEM; database scans; decision making; dynamic information system; effective rule induction; incremental approach; Computer aided software engineering; Data mining; Databases; Heuristic algorithms; Information systems; Set theory; Temperature distribution; ELEM; Global cove; Incremental approach; Rule Induction;

fLanguage

English

Publisher

ieee

Conference_Titel

Electronics Computer Technology (ICECT), 2011 3rd International Conference on

Conference_Location

Kanyakumari

Print_ISBN

978-1-4244-8678-6

Electronic_ISBN

978-1-4244-8679-3

Type

conf

DOI

10.1109/ICECTECH.2011.5941761

Filename

5941761