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Mining XML documents with association rule algorithms
Title:
Mining XML documents with association rule algorithms
Author:
Gürel, Görkem.
Personal Author:
Publication Information:
[s.l.]: [s.n.], 2008.
Physical Description:
x, 63 leaves.: ill. + 1 computer laser optical disc.
Abstract:
Following the increasing use of XML technology for data storage and data exchange between applications, the subject of mining XML documents has become more researchable and important topic. In this study, we considered the problem of Mining Association Rules between items in XML document. The principal purpose of this study is applying association rule algorithms directly to the XML documents with using XQuery which is a functional expression language that can be used to query or process XML data. We used three different algorithms; Apriori, AprioriTid and High Efficient AprioriTid. We give comparisons of mining times of these three apriori-like algorithms on XML documents using different support levels, different datasets and different dataset sizes.
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Added Uniform Title:
Thesis (Master)--İzmir Institute of Technology:Computer Engineering.

İzmir Institute of Technology:Computer Engineering--Thesis (Master).
Electronic Access:
Access to Electronic Version.
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