Set similarity join is a core operation for text data integration, cleaning, and mining. Previous
research work on improving the performance of set similarity joins mostly focused on …

Similarity joins are recognized to be among the most used data processing and analysis
operations. We introduce a C++-based high-level parallel pattern implemented on top of …

Set similarity join is a core operation for text data integration, cleaning, and mining. Most
state-of-the-art solutions rely on inherently sequential, CPU-based algorithms. In this paper …

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 …

Na atual era de Big Data, dados são gerados e coletados em grande velocidade, o que
impõe requisitos severos de desempenho e memória para processamento desses dados …

We consider the problem of efficiently answering set similarity joins over streams. This
problem is challenging both in terms of CPU cost, because similarity matching is …

We consider the problem of efficiently answering set similarity joins over streams. This
problem is challenging both in terms of CPU cost, because similarity matching is …

dc. description. abstract Set similarity join, which finds all the similar set pairs from two
collections of sets, is a fundamental problem with a wide range of applications including …