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Artificial Intelligence Review

Erschienen in:

01.03.2015

XML document clustering: techniques and challenges

verfasst von: Elaheh Asghari, MohammadReza KeyvanPour

Erschienen in: Artificial Intelligence Review | Ausgabe 3/2015

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Abstract

The increasing availability of heterogeneous XML sources has raised a number of issues concerning how to represent and manage these semi-structured data. In recent years due to the importance of managing these resources and extracting knowledge from them, lots of methods have been proposed in order to represent and cluster them in different ways. Different similarity measures have been extended and also in some context semantic issues have been taken into account. In this context, we review different XML clustering methods with considering different representation methods such as tree based and vector based with use of different similarity measures. We also propose taxonomy for these proposed methods.

Vorheriger Artikel Application of reinforcement learning to routing in distributed wireless networks: a review

Nächster Artikel Computational models of emotions for autonomous agents: major challenges

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Titel: XML document clustering: techniques and challenges
verfasst von: Elaheh Asghari
MohammadReza KeyvanPour
Publikationsdatum: 01.03.2015
Verlag: Springer Netherlands
Erschienen in: Artificial Intelligence Review / Ausgabe 3/2015
Print ISSN: 0269-2821
Elektronische ISSN: 1573-7462
DOI: https://doi.org/10.1007/s10462-012-9379-2

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