EFoX: a scalable method for extracting frequent subtrees

Authors:
Juryon Paik;Dong Ryeol Shin;Ungmo Kim
Affiliations:
Dept. of Computer Engineering, Sungkyunkwan University, Suwon-si, Gyeonggi-do, Republic of Korea;Dept. of Computer Engineering, Sungkyunkwan University, Suwon-si, Gyeonggi-do, Republic of Korea;Dept. of Computer Engineering, Sungkyunkwan University, Suwon-si, Gyeonggi-do, Republic of Korea
Venue:
ICCS'05 Proceedings of the 5th international conference on Computational Science - Volume Part III
Year:
2005

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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.