Mining dynamic databases by weighting

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 l...

Teljes leírás

Elmentve itt :
Bibliográfiai részletek
Szerzők: Zhang Shichao
Liu Li
Testületi szerző: Conference for PhD Students in Computer Science (3.) (2002) (Szeged)
Dokumentumtípus: Cikk
Megjelent: 2003
Sorozat:Acta cybernetica 16 No. 1
Kulcsszavak:Számítástechnika, Kibernetika
Tárgyszavak:
Online Access:http://acta.bibl.u-szeged.hu/12716
Leíró adatok
Tartalmi kivonat: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.
Terjedelem/Fizikai jellemzők:179-205
ISSN:0324-721X