Self-organising map techniques for graph data applications to clustering of XML documents

Citation

• Tsoi, A. C., Hagenbuchner, M., & Sperduti, A. (2006). Self-organising map techniques for graph data applications to clustering of XML documents. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 4093 LNAI (pp. 19-30). doi:10.1007/11811305_2

Digital Object Identifier (doi)

• 10.1007/11811305_2

Scopus Eid

• 2-s2.0-33749373226

Web Of Science Accession Number

• WOS:000240088200002

Start Page

• 19

End Page

• 30

Volume

• 4093 LNAI

Issue

Place Of Publication

Abstract

• In this paper, neural network techniques based on Kohonen's self-organising map method which can be trained in an unsupervised fashion and applicable to the processing of graph structured inputs are described. Then it is shown how such techniques can be applied to the problems of clustering of XML documents. �� Springer-Verlag Berlin Heidelberg 2006.

UOW Authors

•   Tsoi, Ah Chung (external author)
•   Hagenbuchner, M.

Publication Date

• 2006

Publisher

• Springer Berlin Heidelberg 

Citation

• Tsoi, A. C., Hagenbuchner, M., & Sperduti, A. (2006). Self-organising map techniques for graph data applications to clustering of XML documents. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 4093 LNAI (pp. 19-30). doi:10.1007/11811305_2

Digital Object Identifier (doi)

• 10.1007/11811305_2

Scopus Eid

• 2-s2.0-33749373226

Web Of Science Accession Number

• WOS:000240088200002

Start Page

• 19

End Page

• 30

Volume

• 4093 LNAI

Issue

Place Of Publication