The main focus of this work is on large set intersection, which is a pivotal operation in
information retrieval, graph analytics and database systems. We aim to experimentally …

Graph pattern mining (GPM) is an important problem in graph processing. There are many
parallel frameworks for GPM, many of which suffer from low performance. GPU is a powerful …

Given two collections of sets, the set similarity join reports all pairs of sets that are within a
given distance threshold. State-of-the-art solutions employ an inverted list index and several …

Exact set similarity join is a notoriously expensive operation, for which several solutions
have been proposed. Recently, there have been studies that present a comparative analysis …

A set similarity join finds all similar pairs from a collection of sets. This operation is essential
for many important tasks in Big Data analytics including string data integration and cleaning …

We investigate the problem of exact set similarity joins using a co-process CPU-GPU
scheme. We focus on large instances of the problem, ie, using datasets of> 1M entries …

In modern application scenarios, large volumes of data are continuously generated over
time at high speeds. Delivering timely analysis results from such massive stream of data …

Set similarity join (SSJ) is a fundamental operation widely used in many application
scenarios, including data discovery, cleaning, and integration. As this operation is …

In the last decade, it has become widely accepted that the performance of modern
processors is no longer limited by transistor density, but by power consumption. As a result …