Zhang Shichao and Liu Li: Mining dynamic databases by weighting. In: Acta cybernetica, (16) 1. pp. 179-205. (2003)
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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 |
| ISSN: | 0324-721X |
| Page Range: | pp. 179-205 |
| Language: | English |
| Place of Publication: | Szeged |
| Event Title: | Conference for PhD Students in Computer Science (3.) (2002) (Szeged) |
| Related URLs: | http://acta.bibl.u-szeged.hu/38515/ |
| Uncontrolled Keywords: | Számítástechnika, Kibernetika |
| Additional Information: | Bibliogr.: p. 204-205. ; összefoglalás angol nyelven |
| Subjects: | 01. Natural sciences 01. Natural sciences > 01.02. Computer and information sciences |
| Date Deposited: | 2016. Oct. 15. 12:25 |
| Last Modified: | 2022. Jun. 15. 08:47 |
| URI: | http://acta.bibl.u-szeged.hu/id/eprint/12716 |
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