DMCA
FRACTURE–Mining: Mining Frequently and Concurrently Mutating Structures from Historical XML Documents
BibTeX
@MISC{Chen_fracture–mining:mining,
author = {Ling Chen and Sourav S. Bhowmick and Liang-tien Chia},
title = {FRACTURE–Mining: Mining Frequently and Concurrently Mutating Structures from Historical XML Documents},
year = {}
}
Share
 |
 |
 |
 |
||
OpenURL
Abstract
In the past few years, the fast proliferation of available XML documents has stimulated a great deal of interest in discovering hidden and nontrivial knowledge from XML repositories. However, to the best of our knowledge, none of existing work on XML mining has taken into account the dynamic nature of XML documents as online information. The present article proposes a novel type of frequent pattern, namely, FRequently And Concurrently muTating substructUREs (FRACTURE), that is mined from the evolution of an XML document. A discovered FRACTURE is a set of substructures of an XML document that frequently change together. Knowledge obtained from FRACTURE is useful in applications such as XML indexing, XML clustering etc. In order to keep the result patterns concise and explicit, we further formulate the problem of maximal FRACTURE mining. Two algorithms, which employ the level-wise and divide-and-conquer strategies respectively, are designed to mine the set of FRACTUREs. The second algorithm, which is more efficient, is also optimized to discover the set of maximal FRACTUREs. Experiments involving a wide range of synthetic and real-life datasets verify the efficiency and scalability of the developed algorithms.
Keyphrases
historical xml document fracture mining xml document xml repository novel type xml mining wide range present article developed algorithm result pattern concise past year maximal fracture mining maximal fracture real-life datasets great deal xml indexing frequent pattern fast proliferation online information available xml document second algorithm discovered fracture nontrivial knowledge divide-and-conquer strategy dynamic nature
