Approximate XML structure validation based on document–grammar tree similarity

Tekli, Joe; Chbeir, Richard; Traina, Agma J. M.; Traina, Caetano; Fileto, Renato

doi:10.1016/j.ins.2014.09.044

Cited by 12 publications

(2 citation statements)

References 59 publications

(190 reference statements)

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“…In the future, we will add a lot of experimental data based on the existing model and consider the XML in the storage and query research. Furthermore, we will validate fuzzy XML based on approximate XML document/grammar tree validation [28,29].…”

Section: Summaries and Discussionmentioning

confidence: 99%

Fuzzy spatio-temporal data modeling based on XML schema

Chen

et al. 2018

Filomat

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With the rapid development of Internet and Big data applications, massive time and space data need to be processed. In order to manage space and time data, the key point is to build a correct data model. There are a lot of fuzzy temporal and spatial information in the real world, and XML has been a useful technology for dealing with various information in the context of Web. In this paper, we first study the fuzzy spatio-temporal data tree by extending the XML Schema and then propose a fuzzy spatio-temporal data model based on XML. Finally, we use the meteorological data to illustrate the validity and usability of the model.

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Section: Summaries and Discussionmentioning

confidence: 99%

Fuzzy spatio-temporal data modeling based on XML schema

Chen

et al. 2018

Filomat

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“…However, requiring optimal results typically causes for too much time to be taken during detection [6,7]. Therefore, many specific applications have been developed that do not achieve optimal results, and many assumptions are used to inform the semantics of a tree [15,18,19], such as whether the tree is ordered [4,16,17,[20][21][22][23][24] or unordered [5,25,26], or whether the tree is labelled [5,20,25] or unlabelled. Nevertheless, no generalized method can be considered to be the best for tree structure-based difference detection, and as a result, much effort has been expended on finding such a generalized method.…”

Section: Difference Detection Of Xml Documentsmentioning

confidence: 99%

A stream-based method to detect differences between XML documents

Jang

Park

2016

Journal of Information Science

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Detecting differences between XML documents is one of most important research topics for XML. Since XML documents are generally considered to be organized in a tree structure, most previous research has attempted to detect differences using tree-matching algorithms. However, most tree-matching algorithms have inadequate performance owing to limitations in terms of the execution time, optimality and scalability. This study proposes a stream-based difference detection method in which an XML binary encoding algorithm is used to provide improved performance relative to that of previous tree-matching algorithms. A tree-structured analysis of XML is not essential in order to detect differences. We use a D-Path algorithm that has an optimal result quality for difference detection between two streams and has a lower time complexity than tree-based methods. We then modify the existing XML binary encoding method to tokenize the stream and the algorithm in order to support more operations than D-Path algorithm does. The experimental results reveal greater efficiency for the proposed method relative to tree-based methods. The execution time is at least 4 times faster than state-of-the-art tree-based methods. In addition, the scalability is much more efficient.

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