A weighted common structure based clustering technique for XML documents

Hwang, Jeong Hee; Ryu, Keun Ho

doi:10.1016/j.jss.2010.02.004

Cited by 11 publications

(8 citation statements)

References 25 publications

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“…These two parameters computation method was illustrated in [1]. For computing the parameter which was in external type, a clustering metric was needed.…”

Section: Clustering Evaluation's Parameters and Notificationsmentioning

confidence: 99%

“…We use two external metrics named F-Measure and Purity as evaluator of our method. More information about this method is mentioned in [1].…”

Section: Introductionmentioning

confidence: 99%

“…This corpus has clustering metric itself which we use it as a comparison versus our external metrics. This corpus could download from references mentioned in [2] and is defined in [1].…”

Section: Introductionmentioning

confidence: 99%

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A Novel Method for Transforming XML Documents to Time Series and Clustering Them Based on Delaunay Triangulation

Shafieian¹

2015

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Nowadays exchanging data in XML format become more popular and have widespread application because of simple maintenance and transferring nature of XML documents. So, accelerating search within such a document ensures search engine's efficiency. In this paper, we propose a technique for detecting the similarity in the structure of XML documents; in the following, we would cluster this document with Delaunay Triangulation method. The technique is based on the idea of representing the structure of an XML document as a time series in which each occurrence of a tag corresponds to a given impulse. So we could use Discrete Fourier Transform as a simple method to analyze these signals in frequency domain and make similarity matrices through a kind of distance measurement, in order to group them into clusters. We exploited Delaunay Triangulation as a clustering method to cluster the d-dimension points of XML documents. The results show a significant efficiency and accuracy in front of common methods.

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“…These two parameters computation method was illustrated in [1]. For computing the parameter which was in external type, a clustering metric was needed.…”

Section: Clustering Evaluation's Parameters and Notificationsmentioning

confidence: 99%

“…We use two external metrics named F-Measure and Purity as evaluator of our method. More information about this method is mentioned in [1].…”

Section: Introductionmentioning

confidence: 99%

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A Novel Method for Transforming XML Documents to Time Series and Clustering Them Based on Delaunay Triangulation

Shafieian¹

2015

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“…Meanwhile, weighted frequent pattern mining also has several applications. First, item weights can be used to calculate the cluster allocation profit, which is the sum of the ratio of total occurrence frequency to the cluster of XML documents, as described in [18]. Second, several efficient recommendation systems [10,13] have been devised based on WFP mining.…”

Section: Introductionmentioning

confidence: 99%

An efficient mining algorithm for maximal weighted frequent patterns in transactional databases

Yun

Shin

Ryu

et al. 2012

Knowledge-Based Systems

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“…It has been utilized as an excellent way of grouping the documents by their content or structure. A lot of efforts have been taken on how to cluster XML documents effectively with structural (Nierman and Jagadish, 2002;Dalamagas et al, 2006;Leung et al, 2005a;Hwang and Ryu, 2010) or semantic (Lee et al, 2001;Nayak and Iryadi, 2007;Tagarelli and Greco, 2004;Kim et al, 2008) information. Hierarchical algorithms (Lian et al, 2004) are based on structural information present in the data.…”

Section: Introductionmentioning

confidence: 99%

Similarity Based Clustering with Indexing for Semi-Structured Document

Mohammad¹

2012

Journal of Computer Science

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Problem statement:To improve the performance of data retrieval in a homogeneous large XML document. Approach: Clustering of XML elements based on the content with indexing. The element which is used for clustering has been identified from the document and/or XML schema. This element is used as a parameter for clustering. The suitable index is created after clustering. Results: The clustering combined with indexing strategy support the efficient retrieval of XML element from the document. Conclusion: The proposed method is used to improve the efficiency of XML data manipulation and comparatively give the better performance rather than clustering or indexing alone.

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A weighted common structure based clustering technique for XML documents

Cited by 11 publications

References 25 publications

A Novel Method for Transforming XML Documents to Time Series and Clustering Them Based on Delaunay Triangulation

A Novel Method for Transforming XML Documents to Time Series and Clustering Them Based on Delaunay Triangulation

An efficient mining algorithm for maximal weighted frequent patterns in transactional databases

Similarity Based Clustering with Indexing for Semi-Structured Document

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