Result: Mining frequent tree-like patterns in large datasets

Title:
Mining frequent tree-like patterns in large datasets
Source:
DASFFA 2005 : database systems for advanced applications (Beijing, 17-20 April 2005)Lecture notes in computer science. :561-567
Publisher Information:
Berlin: Springer, 2005.
Publication Year:
2005
Physical Description:
print, 10 ref
Original Material:
INIST-CNRS
Document Type:
Conference Conference Paper
File Description:
text
Language:
English
Author Affiliations:
Department of Information and Learning Technology, National University of Tainan, Tainan 700, Tawain, Province of China
ISSN:
0302-9743
Rights:
Copyright 2005 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Computer science; theoretical automation; systems
Accession Number:
edscal.16923627
Database:
PASCAL Archive

Further Information

In this paper, we propose a novel data mining scheme to explore the frequent hierarchical structure patterns, named tree-like patterns, with the relationship of each item on a sequence. By tree-like patterns, we are clear to find out the relation of items between the cause and effect. Finally, we discuss the different characteristics to our mined patterns with others. As a consequence, we can find out that our addressed tree-like patterns can be widely used to explore a variety of different applications.