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This is a guest post by Russell Waterson, Knowledge Graph Engineer at Data Lens Ltd. Customers use knowledge graphs to consolidate and integrate information assets and make them more readily available. Building knowledge graphs by getting data from disparate existing data sources can be expensive, time-consuming, and complex. Project planning, project management, engineering, maintenance and […]

Stanford / Winter 2021

Knowledge graphs bring vital changes to connected inventories for financials and enable them to save much time and expenses

I recently purchased a new laptop one with enough speed and space to let me do any number of projects that my nearly four-year-old workhorse was just not equipped to handle.

How simple structured data trumps clever machine learning

On the role of knowledge that is structured, explicit and intelligible in providing a path toward higher machine intelligence

I worked on some experiments on RDF-to-text generation. The goal is to generate coherent multi-sentence texts from data in a knowledge graph. While not...

This demo allows hands-on experience on Knowledge Graph databases by executing SPARQL queries side-by-side with their SQL counterparts.

Tracing the triumphs and challenges of two decades of Semantic Web research and applications.

Basic Introduction to what Graph Analytics is…

Read about how knowledge graphs can unlock meaning and thus create a smart future-proof living repository of scientific data and its relationships.

This blog highlights some of the new automation features that Cambridge Semantics is building into our scalable knowledge graph platform - Anzo.

Although artificial intelligence capabilities are improving daily, it is not always easy to put the AI rubber on the road – especially when it comes to understanding AI’s contextual data and problem-solving approaches. How about bringing in some “real” intelligence? Graphs are a typically human way

Multi-Model Database Use Case

We kicked off our #NeurIPS2020 series joined by @TacoCohen, ML Researcher at @Qualcomm @Qualcomm_Tech, to discuss his current research in equivariant networks and video compression using generative models, as well as his paper “Natural Graph Networks.”— The TWIML AI Podcast (@twimlai) December 22, 2020

Modelling complex relationships in RDF graphs

Background

For the last few years, I have been promoting the idea of the Hardware Graph. My assertion was that graph hardware needs a focus on simple…

Solutions Review has compiled this list of the best graph databases to consider based on real user reviews and product roadmaps.

Stardog launches the industry's first cloud-native Enterprise Knowledge Graph Platform.

"Inrupt ... has launched its first enterprise-ready Solid servers for use by more than a dozen partners, including the NHS, the BBC and NatWest Bank." https://t.co/HcW0uWJjUZ— Aaron Bradley (@aaranged) November 10, 2020

The ICIJ used Neo4j to expose a vast money laundering network running through Western banks. This blog analyzes the FinCEN Files data.

“How do you select a graph database? Learn how in @itworldca. Read here: https://t.co/Z529PWdeW6 | #GraphDatabase #GraphDB #GraphAnalytics #DataScience #Developer #Analytics #BigData”

TopQuadrant CEO, Irene Polikoff, provides an overview of the two main graph models along with illustrations of their similarities and differences in graph diagrams in Part I of II in this article series from @TDAN_com https://t.co/CxOrTb3ELL#knowledgegraphs #datagovernance— TopQuadrant (@TopQuadrant) September 25, 2020

I'll be discussing "Graph Queries with Gremlin Language Variants" at the Category Theory and Applications group meetup on October 6: https://t.co/MG1HpNEiGd Be prepared to see Gremlin in many different forms! #graphdb pic.twitter.com/OIOsfLvWze— stephen mallette (@spmallette) September 28, 2020