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 ...

Dr. Alin Deutsch of UC San Diego explains in a Q&A why graph database algorithms will become the driving force behind the next generation of AI and machine learning apps.

Graph data science is when you want to answer questions, not just with your data, but with the connections between your data points — that’s the 30-second explanation, according to Alicia Frame.

Forbes contributors publish independent expert analyses and insights. I write about blockchain and big data, primarily focusing on XRP. By applying a well-known graph algorithm to the XRP ledger ...

Graph databases’ best applications, he said, appear where query processing across complex networks of relationships is vital. He cites MDM, transport logistics and data lineage as such examples.

Knowledge graphs are hyped. We can officially say this now, since Gartner included knowledge graphs in the 2018 hype cycle for emerging technologies. Though we did not have to wait for Gartner ...

They know what can and cannot be done with data and how to interpret and visualise data and algorithms to provide information for real impact. At the beginning of this year, UN Global Pulse worked ...

Cross-listed with DTSA 5503 Course Type: Pathway | Breadth Specialization: Foundations of Data Structures and Algorithms Instructor: Dr. Sriram Sankaranarayanan, Professor of Computer Science Prior ...

The Graph 500 was created to chart how well the world’s largest computers handle such data intensive workloads. The latest edition of the list was released at the SC12 supercomputing conference ...