Dynamic graph algorithms and data structures represent a vital research frontier in computer science, underpinning applications from network analysis to real-time system monitoring. These methods ...

Forbes contributors publish independent expert analyses and insights. I track enterprise software application development & data management. Jul 03, 2025, 10:43am EDT Business 3d tablet virtual growth ...

Graph theory isn’t enough. The mathematical language for talking about connections, which usually depends on networks — vertices (dots) and edges (lines connecting them) — has been an invaluable way ...

When we ask Siri, Alexa or Google Home a question, we often get alarmingly relevant answers. Why? And more importantly, why don’t we get the same quality of answers and smooth experience in our ...

Graph databases are the fastest growing category in all of data management, according to DB-Engines.com, a database consultancy. Since seeing early adoption by companies including Twitter, Facebook ...

Neo4j, a provider of graph technology, is launching Neo4j for Graph Data Science, a data science environment built to harness the predictive power of relationships for enterprise deployments. Neo4j ...

Redis may be ubiquitous as a persistent caching tier, but Redis Labs, the company behind it, wants you to think about it as an operational database that is extensible. This is quite true, and it's the ...

In recent years, knowledge graphs have become an important tool for organizing and accessing large volumes of enterprise data in diverse industries — from healthcare to industrial, to banking and ...

As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models designed to process graph-structured data. Currently, GNNs are effective ...