Matching hierarchical classifications with attributes

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Abstract

Hierarchical Classifications with Attributes are tree-like structures used for organizing/classifying data. Due to the exponential growth and distribution of information across the network, and to the fact that such information is usually clustered by means of this kind of structures, we assist nowadays to an increasing interest in finding techniques to define mappings among such structures. In this paper, we propose a new algorithm for discovering mappings across hierarchical classifications, which faces the matching problem as a problem of deducing relations between sets of logical terms representing the meaning of hierarchical classification nodes. © Springer-Verlag Berlin Heidelberg 2006.

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APA

Serafini, L., Zanobini, S., Sceffer, S., & Bouquet, P. (2006). Matching hierarchical classifications with attributes. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4011 LNCS, pp. 4–18). Springer Verlag. https://doi.org/10.1007/11762256_4

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