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A Weighted‐Tree Similarity Algorithm for Multi‐Agent Systems in E‐Business Environments
Author(s) -
Bhavsar Virendrakumar C.,
Boley Harold,
Yang Lu
Publication year - 2004
Publication title -
computational intelligence
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.353
H-Index - 52
eISSN - 1467-8640
pISSN - 0824-7935
DOI - 10.1111/j.0824-7935.2004.00255.x
Subject(s) - computer science , tree traversal , serialization , similarity (geometry) , tree (set theory) , theoretical computer science , xml , algorithm , node (physics) , artificial intelligence , data mining , programming language , mathematics , image (mathematics) , mathematical analysis , operating system , structural engineering , engineering
A tree similarity algorithm for match‐making of agents in e‐Business environments is presented. Product/service descriptions of seller and buyer agents are represented as node‐labeled, arc‐labeled, arc‐weighted trees. A similarity algorithm for such trees is developed as the basis for semantic match‐making in a virtual marketplace. The trees are exchanged using an XML serialization in Object‐Oriented RuleML. Correspondingly, we use the declarative language Relfun to implement the similarity algorithm as a parameterized, recursive functional program. Three main recursive functions perform a top‐down traversal of trees and the bottom‐up computation of similarity. Results from our experiments aiming to match buyers and sellers are found to be effective and promising for e‐Business/e‐Learning environments. The algorithm can be applied in all environments where weighted trees are used.