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EXiT-B: A New Approach for Extracting Maximal Frequent Subtrees from XML Data

2005; Springer Science+Business Media; Linguagem: Inglês

10.1007/11508069_1

1611-3349

Juryon Paik, Dongho Won, Farshad Fotouhi, Ung Mo Kim,

Data Management and Algorithms

Along with the increasing amounts of XML data available, the data mining community has been motivated to discover the useful information from the collections of XML documents. One of the most popular approaches to find the information is to extract frequent subtrees from a set of XML trees. In this paper, we propose a novel algorithm, EXiT-B, for efficiently extracting maximal frequent subtrees from a set of XML documents. The main contribution of our algorithm is that there is no need to perform tree join operation during the phase of generating maximal frequent subtrees. Thus, the task of finding maximal frequent subtrees can be significantly simplified comparing to the previous approaches.