Earticle

초록

영어

To extract structural features from tree-structured documents among nodes in which characteristic words appear, we described a text-mining algorithm for enumerating all frequent consecutive path patterns (CPP) on a list W of words in Uchida et al., PAKDD 2004 [14]. In this paper, we first extend a CPP to a tree pattern, which is called a tree association pattern (TAP), over a set W of words. A TAP is an ordered rooted tree t such that the root of t has no child or at least two children, all leaves of t are labeled with non-empty subsets of W and all internal nodes, if they exist, are labeled with strings. By modifying text-mining algorithms to find all frequent CPPs, next, we present text-mining algorithms for enumerating all maximal frequent TAPs in tree-structured documents, where a TAP t is maximal if there exists no frequent TAP, which has t as a proper subpattern. Then, we tested our algorithms using Reuters news wires. Finally, as one application of CPPs, we present an algorithm for a wrapper based on CPP using XSLT transformation language and demonstrate simply the use of the wrapper to translate one of the Reuters news wires into other XML document.

목차

Abstract
 1. Introduction
 2. Consecutive path pattern
 3. Tree association pattern
 4. Enumerating all maximal frequent TAPs from tree-structureddocuments
  4.1 Text-mining algorithm for maximal frequent TAPs problem
  4.2 Experimental results
 5. Generating XSLT stylesheets based on CPP
 6. Conclusion and future works
 References

키워드

저자

• Tomoyuki Uchida [ Faculty of Information Sciences, Hiroshima City University ]
• Kayo Kawamoto [ Faculty of Information Sciences, Hiroshima City University ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Database Theory and Application

• 간기

  격월간

• pISSN

  2005-4270

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605