In this chapter, we will provide a survey of clustering algorithms for graph data. We will
discuss the different categories of clustering algorithms and recent efforts to design …

Graph data models enable efficient storage, visualization, and analysis of highly interlinked
data, by providing the benefits of horizontal scalability and high query performance …

With the increasing number of available XML documents, numerous approaches for retrieval
have been proposed in the literature. They usually use the tree representation of documents …

XML has become a popular method of data representation both on the web and in
databases in recent years. One of the reasons for the popularity of XML has been its ability …

Graph mining and management has become a popular area of research in recent years
because of its numerous applications in a wide variety of practical fields, including …

This book focuses on the basic concepts and the related technologies of data mining for
social medial. Topics include: big data and social data, data mining for making a hypothesis …

In this paper, we will examine the problem of clustering massive graph streams. Graph
clustering poses significant challenges because of the complex structures which may be …

Modern computing systems are instrumented to generate huge amounts of system logs and
these data can be utilized for understanding and complex system behaviors. One main …

Keyword search enables Web users to easily access XML data without the need to learn a
structured query language and to study possibly complex data schemas. Existing work has …

XML has become a de facto standard for data representation and exchange over the
Internet. With the emergence of more and more XML documents, the clustering of XML …