EFoX: A scalable method for extracting frequent subtrees

5Citations
Citations of this article
4Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

The more web data sources provide XML data, the greater information flood problem has been caused. Hence, there have been increasing demands for efficient methods of discovering desirable patterns from a large collection of XML data. In this paper, we propose a new and scalable algorithm, EFoX, to mine frequently occurring tree patterns from a set of labeled trees. The main contribution made by our algorithm is that there is no need to perform any tree join operation to generate candidate sets. © Springer-Verlag Berlin Heidelberg 2005.

Cite

CITATION STYLE

APA

Paik, J., Shin, D. R., & Kim, U. (2005). EFoX: A scalable method for extracting frequent subtrees. In Lecture Notes in Computer Science (Vol. 3516, pp. 813–817). Springer Verlag. https://doi.org/10.1007/11428862_113

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free