MOD

Graph neural networks (GNNs) have received more and more attention in past several years, due to the wide applications of graphs and networks, and the superiority of their performance compared to traditional heuristics-driven approaches. However, most ...

More and more knowledge graphs are becoming available on the Web, many of them accessible via queryable interfaces, such as SPARQL endpoints. These knowledge graphs are often linked to each other and in doing so form the so-called Web of Data. The great ...

Graphs and graph-processing have become increasingly important. This has led to an explosion in the development of graph-processing systems, each of which is evaluated relative to its predecessors. In the absence of a large corpus of real-world graphs, ...

We describe the design and implementation of EdgeFrame: a graph-specialized Spark DataFrame that caches the edges of a graph in compressed form on all worker nodes of a cluster, and provides a fast and scalable Worst-Case-Optimal Join (WCOJ) that is ...

A recent study showed that the applicability of context-free path querying (CFPQ) algorithms with relational query semantics integrated with graph databases is limited because of low performance and high memory consumption of existing solutions. In this ...

Vertex-centric block synchronous processing systems, exemplified by Pregel and Giraph, have received extensive attention for graph processing. These systems allow programmers to think only about operations that take place at one vertex and provide the ...

Classically, ML models trained with stochastic gradient descent (SGD) are designed to minimize the average loss per example and use a distribution of training examples that remains static in the course of training. Research in recent years demonstrated, ...

Many data processing pipelines operate on highly-connected data sets that can be efficiently modelled as graphs. These graphs are rarely static, but rather change rapidly and often exhibit dynamic, temporal, or streaming behaviour. During the last ...

We present the design overview of a pattern matching engine for labeled graphs that supports interactive search: the user, based on feedback received from the search system, repeatedly revises her search template until s/he is satisfied with the ...

In this paper, we demonstrate a framework for DSL-based SQL query classification according to data-privacy directives. Based on query-log analysis, this framework automatically derives query meta-information (QMI) and provides interfaces for browsing ...

In this demonstration paper, we present the Graph Based Benchmark Suite (GBBS), a suite of scalable, provably-efficient implementations of over 20 fundamental graph problems for shared-memory multicore machines. Our results are obtained using a graph ...