Presentation 2005-02-24
Merging Shock Trees Using Alignable Mappings
Tetsuji KUBOYAMA, Kilho SHIN, Tetsuhiro MIYAHARA,
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Abstract(in English) A shock tree is a very effective characterization for representing 2D shapes. Torsello and Hancock have proposed an unsupervised learning method of tree structures for shock tree matching. The core procedure of this method is based on merging two trees using a tree edit distance measure. This method, however, does not guarantee that the structure obtained by the merging is also a tree. Then the method adopts an ad-hoc way, which discards the result unless it is a tree, and tries with the other pair of trees. This paper shows the critical condition to obtain a tree structure by merging two trees. The condition is obtained by showing that alignment of trees is identical to a variant of edit distance, called less-constrained edit distance. In addition, we study a condition for yielding a unique supertree of two trees.
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Keyword(in English) tree edit distance / alignment of trees / shock trees
Paper # NLC2004-113,PRMU2004-195
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Committee NLC
Conference Date 2005/2/17(1days)
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Registration To Natural Language Understanding and Models of Communication (NLC)
Language ENG
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Merging Shock Trees Using Alignable Mappings
Sub Title (in English)
Keyword(1) tree edit distance
Keyword(2) alignment of trees
Keyword(3) shock trees
1st Author's Name Tetsuji KUBOYAMA
1st Author's Affiliation Center for Collaborative Research, The University of Tokyo()
2nd Author's Name Kilho SHIN
2nd Author's Affiliation Research Center for Advanced Science and Technology, The University of Tokyo
3rd Author's Name Tetsuhiro MIYAHARA
3rd Author's Affiliation Faculty of Information Sciences, Hiroshima City University
Date 2005-02-24
Paper # NLC2004-113,PRMU2004-195
Volume (vol) vol.104
Number (no) 667
Page pp.pp.-
#Pages 6
Date of Issue