Treffer: XML clustering based on common neighbor
Title:
XML clustering based on common neighbor
Authors:
Source:
Advanced Web and Network Technologies, and Applications (APWeb 2006 international workshops)Lecture notes in computer science. :137-141
Publisher Information:
Berlin; New York, NY: Springer, 2006.
Publication Year:
2006
Physical Description:
print, 8 ref 1
Original Material:
INIST-CNRS
Subject Terms:
Computer science, Informatique, Sciences exactes et technologie, Exact sciences and technology, Sciences appliquees, Applied sciences, Informatique; automatique theorique; systemes, Computer science; control theory; systems, Logiciel, Software, Systèmes informatiques et systèmes répartis. Interface utilisateur, Computer systems and distributed systems. User interface, Analyse amas, Cluster analysis, Analisis cluster, Classification, Clasificación, Fouille donnée, Data mining, Busca dato, Langage XML, XML language, Lenguaje XML, Observation aberrante, Outlier, Observación aberrante, Structure document, Document structure, Estructura documental
Document Type:
Konferenz
Conference Paper
File Description:
text
Language:
English
Author Affiliations:
College of Computer Science and Technology, Jilin University, Changchun, China
College of Computer Science and Technology, Harbin Engineering University, Harbin, China
College of Computer Science and Technology, Harbin Engineering University, Harbin, China
ISSN:
0302-9743
Rights:
Copyright 2007 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
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.19151821
Database:
PASCAL Archive
Weitere Informationen
Clustering on XML documents is an important task. However, it is difficult to select the appropriate parameters' value for the clustering algorithms. By integrating outlier detection with clustering, the paper takes a new approach for analyzing the XML documents by structure distance. After stating the XML tree distance, the paper proposes a new clustering algorithm, which stops clustering automatically by utilizing the outlier information and needs only one parameter, whose appropriate value range can be decided in the outlier mining process. The paper adopts the XML dataset with different structure and other real-life datasets to compare it with other clustering algorithms.