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. © Springer-Verlag Berlin Heidelberg 2005.
CITATION STYLE
Giugno, R., Pulvirenti, A., & Reforgiato Recupero, D. (2005). Clustered trie structures for approximate search in hierarchical objects collections. In Lecture Notes in Computer Science (Vol. 3686, pp. 63–70). Springer Verlag. https://doi.org/10.1007/11551188_7
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