The explosion in the amount of the available RDF data has lead to the need to explore,
query and understand such data sources. Due to the complex structure of RDF graphs and …

Graph data modeling and querying arises in many practical application domains such as
social and biological networks where the primary focus is on concepts and their …

To measure the similarity of nodes in the neighboring subgraphs, Milner introduced the
notion of k-limited bisimilarity. Recently, as a weaker version of k-limited bisimilarity, the …

RDF knowledge base summarization produces a compact and faithful abstraction for
entities, relations, and ontologies. The summary is critical to a wide range of knowledge …

Computing containment relations between massive collections of sets is a fundamental
operation in data management, for example in graph analytics and data mining applications …

Graph summarization is the process of computing a compact version of an input graph while
preserving chosen features of its structure. We consider semantic graphs where the features …

Bisimulation provides structural conditions to characterize indistinguishability from an
external observer between nodes on labeled graphs. It is a fundamental notion used in …

Big Data Streams are very popular at now, as stirred-up by a plethora of modern
applications such as sensor networks, scientific computing tools, Web intelligence, social …

The explosive growth of RDF data makes it difficult to be efficiently queried, understood and
used. RDF graph (RDFG) summarization aims to extract the most relevant and crucial data …

Large data graphs with complex and heterogeneous structure, possibly featuring typed data
and an ontol-ogy encoding the application-domain semantics, are widely used nowadays …