Clustered trie structures for approximate search in hierarchical objects collections

Authors:
R. Giugno;A. Pulvirenti;D. Reforgiato Recupero
Affiliations:
Computer Science Department, University of Catania, Catania, Italy;Computer Science Department, University of Catania, Catania, Italy;Computer Science Department, University of Catania, Catania, Italy
Venue:
ICAPR'05 Proceedings of the Third international conference on Advances in Pattern Recognition - Volume Part I
Year:
2005

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Abstract

Rapid developments in science and engineering are producing a profound effect on the way information is represented. A new problem in pattern recognition has emerged: new data forms such as trees representing XML documents and images cannot been treated efficiently by classical storing and searching methods. In this paper we improve trie-based data structures by adding data mining techniques to speed up range search process. Improvements over the search process are expressed in terms of a lower number of distance calculations. Experiments on real sets of hierarchically represented images and XML documents show the good behavior of our patter recognition method.