… This book is designed for studying various applications in the context of managing and
mining graphs. … Where possible, we have clarified the connections with the methods and …

… the goals and the means for developing a general purpose graph system. We highlight the
challenges posed by the graph data, the constraints of architectural design, the different types …

… out in the integrated data and process graph and to assist users by … graph-based model
for sharing and mining scenarios. In Section 6, we introduce a data dependency-based mining …

… mining algorithms. In this chapter, we will provide a survey of dif- ferent kinds of graph mining
and management algorithms… upon graph representations. We will discuss how the different …

… We note that XML data is quite similar to graph data in terms of how the data is organized
structurally. The attribute values can be treated as graph labels and the corresponding semi-…

… , and dynamic graphs. Then we describe important tools for large graph mining, including
singular … Finally, we conclude with the design and the implementation of scalable graph mining …

… In particular we discuss graph database systems and their main graph data models,
namely the resource description framework [63] and the property graph model [93] (Sect. 2). …

… Graph analytics can be divided into three parts – graph data management, graph modeling,
and graph mining. In this section, fundamentals of each of the three parts are discussed in …

… for Big Data analytics with a focus on graph data. We first presented large scale data mining
… Then, we presented graph processing frameworks and current pattern mining techniques in …

… to investigate the potential of graph data and graph mining techniques in the building field.
A graph-based methodology is proposed to analyze building operational data. It consists of …