A new sequential mining approach to XML document similarity computation1

Ho Pong Leung; Fu Lai Korris Chung; Stephen Chi Fai Chan

A new sequential mining approach to XML document similarity computation1

Ho Pong Leung, Fu Lai Korris Chung, Stephen Chi Fai Chan

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

5 Citations (Scopus)

Abstract

There exist several methods to measuring the structural similarity among XML documents. The data mining approach seems to be a novel, interesting and promising one. In view of the deficiencies encountered by ignoring the hierarchical information in encoding the paths for mining, we propose a new sequential pattern mining scheme for XML document similarity computation. It makes use of the hierarchical information to computing the document structural similarity. In addition, it includes a post-processing step to reuse the mined patterns to estimate the similarity of unmatched elements so that another metric to qualify the similarity between XML documents can be introduced. Encouraging experimental results were obtained and reported.

Original language	English
Title of host publication	Advances in Knowledge Discovery and Data Mining
Publisher	Springer Verlag
Pages	356-362
Number of pages	7
Volume	2637
ISBN (Electronic)	3540047603, 9783540047605
Publication status	Published - 1 Jan 2003
Event	7th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2003 - Seoul, Korea, Republic of Duration: 30 Apr 2003 → 2 May 2003

Conference

Conference	7th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2003
Country/Territory	Korea, Republic of
City	Seoul
Period	30/04/03 → 2/05/03

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

Cite this

@inproceedings{a672ac98b960492583a569c753c786eb,

title = "A new sequential mining approach to XML document similarity computation1",

abstract = "There exist several methods to measuring the structural similarity among XML documents. The data mining approach seems to be a novel, interesting and promising one. In view of the deficiencies encountered by ignoring the hierarchical information in encoding the paths for mining, we propose a new sequential pattern mining scheme for XML document similarity computation. It makes use of the hierarchical information to computing the document structural similarity. In addition, it includes a post-processing step to reuse the mined patterns to estimate the similarity of unmatched elements so that another metric to qualify the similarity between XML documents can be introduced. Encouraging experimental results were obtained and reported.",

author = "Leung, {Ho Pong} and Chung, {Fu Lai Korris} and Chan, {Stephen Chi Fai}",

year = "2003",

month = jan,

day = "1",

language = "English",

volume = "2637",

pages = "356--362",

booktitle = "Advances in Knowledge Discovery and Data Mining",

publisher = "Springer Verlag",

address = "Germany",

note = "7th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2003 ; Conference date: 30-04-2003 Through 02-05-2003",

}

A new sequential mining approach to XML document similarity computation1. / Leung, Ho Pong; Chung, Fu Lai Korris; Chan, Stephen Chi Fai.
Advances in Knowledge Discovery and Data Mining. Vol. 2637 Springer Verlag, 2003. p. 356-362.

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

TY - GEN

T1 - A new sequential mining approach to XML document similarity computation1

AU - Leung, Ho Pong

AU - Chung, Fu Lai Korris

AU - Chan, Stephen Chi Fai

PY - 2003/1/1

Y1 - 2003/1/1

N2 - There exist several methods to measuring the structural similarity among XML documents. The data mining approach seems to be a novel, interesting and promising one. In view of the deficiencies encountered by ignoring the hierarchical information in encoding the paths for mining, we propose a new sequential pattern mining scheme for XML document similarity computation. It makes use of the hierarchical information to computing the document structural similarity. In addition, it includes a post-processing step to reuse the mined patterns to estimate the similarity of unmatched elements so that another metric to qualify the similarity between XML documents can be introduced. Encouraging experimental results were obtained and reported.

AB - There exist several methods to measuring the structural similarity among XML documents. The data mining approach seems to be a novel, interesting and promising one. In view of the deficiencies encountered by ignoring the hierarchical information in encoding the paths for mining, we propose a new sequential pattern mining scheme for XML document similarity computation. It makes use of the hierarchical information to computing the document structural similarity. In addition, it includes a post-processing step to reuse the mined patterns to estimate the similarity of unmatched elements so that another metric to qualify the similarity between XML documents can be introduced. Encouraging experimental results were obtained and reported.

UR - http://www.scopus.com/inward/record.url?scp=7444241465&partnerID=8YFLogxK

M3 - Conference article published in proceeding or book

VL - 2637

SP - 356

EP - 362

BT - Advances in Knowledge Discovery and Data Mining

PB - Springer Verlag

T2 - 7th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2003

Y2 - 30 April 2003 through 2 May 2003

ER -

A new sequential mining approach to XML document similarity computation1

Abstract

Conference

ASJC Scopus subject areas

Other files and links

Fingerprint

Cite this