On-the-Fly Output Compression for Join-Based Graph Mining Algorithms

Join-Graph Propagation Algorithms

The paper investigates parameterized approximate message-passing schemes that are based on bounded inference and are inspired by Pearl's belief propagation algorithm (BP). We start with the bounded inference mini-clustering algorithm and then move to the iterative scheme called Iterative Join-Graph Propagation (IJGP), that combines both iteration and bounded inference. Algorithm IJGP belongs to...

Multipredicate Join Algorithms for Accelerating Relational Graph Processing on GPUs

Recent work has demonstrated that the use of programmable GPUs can be advantageous during relational query processing on analytical workloads. In this paper, we take a closer look at graph problems such as finding all triangles and all four-cliques of a graph. In particular, we present two different join algorithms for the GPU. The first is an implementation of Leapfrog-Triejoin (LFTJ), a recen...

GraphZip: Dictionary-based Compression for Mining Graph Streams

A massive amount of data generated today on platforms such as social networks, telecommunication networks, and the internet in general can be represented as graph streams. Activity in a network’s underlying graph generates a sequence of edges in the form of a stream; for example, a social network may generate a graph stream based on the interactions (edges) between di‚erent users (nodes) over t...

Web-graph Pre-compression for Similarity Based Algorithms

The size of web-graph created from crawling the web is an issue for every search engine. The amount of data gathered by web crawlers makes it impossible to load the web-graph into memory which increases the number of I/O operations. Compression can help reduce run-time of web-graph processing algorithms. We introduce a new algorithm for compressing the link structure of the web graph by groupin...

Novel Graph Based Clustering and Visualization Algorithms for Data Mining