Affiliation:
1. Department of Information Science, Utsunomiya University 2753 Ishiimachi, Utsunomiya 321, Japan
Abstract
This paper describes the computing alogrithms for the tree distance based on the structure preserving mapping. The distance is defined as the minimum sum of the weights of edit operations needed to transform tree Tα to tree Tβ under restriction of the structure preserving mapping. The edit operations allow substituting a vertex of a tree to another, deleting a vertex of a tree and inserting a vertex to a tree. Proposed algorithms determine the distance between Tα and Tβ in time O(NαNβLα) or O(NαNβLβ), and in space O(NαNβ), where Nα, Nβ, Lα and Lβ are the number of vertices of Tα, Tβ, the number of’ leaves of Tα and Tβ, respectively. The time complexity is close to the unapproachable lowest bound O(NαNβ). Improved algorithms are presented. This tree distance can be applied to any problems including pattern recognition, syntactic tree comparison and classification, and tree comparison whose structures are important in structure preserving mapping.
Publisher
World Scientific Pub Co Pte Lt
Subject
Artificial Intelligence,Computer Vision and Pattern Recognition,Software
Cited by
38 articles.
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