Mining dynamic databases by weighting

Zhang, Shichao and Liu, Li: Mining dynamic databases by weighting. Acta cybernetica, (16) 1. pp. 179-205. (2003)

[img] Cikk, tanulmány, mű
cybernetica_016_numb_001_179-205.pdf

Download (1MB)

Abstract

A dynamic database is a set of transactions, in which the content and the size can change over time. There is an essential difference between dynamic database mining and traditional database mining. This is because recently added transactions can be more 'interesting' than those inserted long ago in a dynamic database. This paper presents a method for mining dynamic databases. This approach uses weighting techniques to increase efficiency, enabling us to reuse frequent itemsets mined previously. This model also considers the novelty of itemsets when assigning weights. In particular, this method can find a kind of new patterns from dynamic databases, referred to trend patterns. To evaluate the effectiveness and efficiency of the proposed method, we implemented our approach and compare it with existing methods.

Item Type: Article
Journal or Publication Title: Acta cybernetica
Date: 2003
Volume: 16
Number: 1
Page Range: pp. 179-205
ISSN: 0324-721X
Language: angol
Uncontrolled Keywords: Természettudomány, Informatika
Additional Information: Bibliogr.: p. 204-205.; Abstract
Date Deposited: 2016. Oct. 15. 12:25
Last Modified: 2018. Apr. 11. 17:04
URI: http://acta.bibl.u-szeged.hu/id/eprint/12716

Actions (login required)

View Item View Item