Abstract: Given a set of data graphs and a query graph, graph isomorphism query processing is the problem of finding all the data graphs that are isomorphic to the query graph. Graph isomorphism query ...

While it is easy to learn and understand the Cypher declarative language for querying graph databases, it can be very difficult to master it. As graph databases are becoming more mainstream, there is ...

A monthly overview of things you need to know as an architect or aspiring architect. Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with ...

Select the journal/section where you want your idea to be submitted: The interplay between graph analytics and large language models (LLMs) represents a promising frontier for advancing knowledge ...

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Dany Lepage discusses the architectural ...

In recent years, with the rapid development of technologies such as mobile internet, the internet of things, social networks, and big data processing, various industries have begun to generate vast ...

To this end, we propose a personalized graph signal processing (PGSP) method for collaborative filtering. Firstly, we design the personalized graph signal containing richer user information and ...

A new open-source library by Nvidia could be the secret ingredient to advancing analytics and making graph databases faster. The key: parallel processing on Nvidia GPUs. Nvidia has long ago stopped ...

🎉 Big News! Thrilled to announce that three of our papers have been accepted at SIGMOD, the top-tier conference for database systems! 🚀 Here’s what we’re bringing to the table: • GES: ...

If you look back at it now, especially with the advent of massively parallel computing on GPUs, maybe the techies at Tera Computing and then Cray had the right idea with their “ThreadStorm” massively ...