A Research Growth Study in Big Data field

Responding to the diffusion and growth of big data research, this study adopted the bibliometric approach to describe the growth of the literatures, the distribution of journals, publication countries and subject area. This study collected the relative literature by querying the Social Science Citation Index (SSCI) of ISI Web of knowledge database, where we could collect the big data literatures in academic papers, systematically. Data from citation indexes can be analyzed to determine the popularity and impact of specific articles, authors, and publications. The results provided the distribution of core journals, and described the trends and feature of big data research for researchers interested in this field

An introduction to Graph Data Management

A graph database is a database where the data structures for the schema and/or instances are modeled as a (labeled)(directed) graph or generalizations of it, and where querying is expressed by graph-oriented operations and type constructors. In this article we present the basic notions of graph databases, give an historical overview of its main development, and study the main current systems that implement them

Graph Summarization

The continuous and rapid growth of highly interconnected datasets, which are both voluminous and complex, calls for the development of adequate processing and analytical techniques. One method for condensing and simplifying such datasets is graph summarization. It denotes a series of application-specific algorithms designed to transform graphs into more compact representations while preserving structural patterns, query answers, or specific property distributions. As this problem is common to several areas studying graph topologies, different approaches, such as clustering, compression, sampling, or influence detection, have been proposed, primarily based on statistical and optimization methods. The focus of our chapter is to pinpoint the main graph summarization methods, but especially to focus on the most recent approaches and novel research trends on this topic, not yet covered by previous surveys.Comment: To appear in the Encyclopedia of Big Data Technologie