In recent years, processing and analysing large graphs has become a major need in many research areas. Distributed graph processing programming models and frameworks arised as a natural solution to process linked data of ...

Due to their fine-grained operations and low conflict rates, graph processing algorithms expose a large amount of parallelism that has been extensively exploited by various parallelization frameworks. Transactional Memory ...

The creation of new and better recommendation algorithms for social networks is currently receiving much attention owing to the increasing need for new tools to assist users. The volume of available social data as well as ...

Large-scale graphs have become ubiquitous in social media. Computer-based recommendations in these huge graphs pose challenges in terms of algorithm design and resource usage efficiency when processing recommendations in ...

Data Analytics involves applying algorithmic processes to derive insights. Nowadays it is used in many industries to allow organizations and companies to make better decisions as well as to verify or disprove existing ...

Process automation and applications integration initiatives are oftencomplex and involve significant resources in large organisations. The increasing adoption of service-based architectures to solve integration problems ...

Several real-world situations can be modeled in graphs, such as road maps, electricity and water supply networks, relationships among users of social networks, among others. With nearly global reach of technology, it is ...

Software process learning is a relevant aspect on software process improvement. In this paper, we present a framework based on knowledge graphs, in order to evaluate the expertise on ISO 15504 software model (SPICE). Having ...