Knowledge Graph

A new milestone in graph data management — We introduce the concept of Neural Graph Databases as the next step in the evolution of graph databases. Tailored for large incomplete graphs and on-the-fly inference of missing edges using graph representation learning, neural reasoning maintains high expressiveness and supports complex logical queries similar to standard graph query languages. This…

This article is section 3.2 of part 3 of the Introduction to knowledge graphs series of articles. A number of languages have been proposed for querying graphs, including the SPARQL query language for RDF graphs; and Cypher, Gremlin, and G-CORE[1] for querying property graphs. …

Any database is pretty useless unless the user can ask, and get answers to, their questions. KnowledgeGraphs are superb at representing a domain’s data, and, together with a model, can deliver answers, though the questions need to be formulated as a query by an expert. Conversely, Large Language Models (LLM)…

This week we feature content from OpenAI and Kurt Cagle. Additional reading comes from Alex Hollender, Dean Allemang, and Tom Warren. News comes from Adobe, Ontotext, Kobai, and Syncro Soft. Note that news items now link to the original source of the news rather than our 200 word summaries, which…

This article is section 3.1 of part 3 of the Introduction to knowledge graphs series of articles. Graphs offer a flexible way to conceptualise, represent, and integrate diverse and incomplete data. …

I have been doing successful knowledge graph deployments with my clients for just a bit over ten years; usually with one of the big banks, but also in pharmaceutical companies and media companies. There’s a pattern to how a lot of these projects go, and that pattern makes use of…

** There be heavy philosophical pondering ahead!** I wrote this a while ago and found it a bit all over the place. But it gets at an idea that I find fascinating. How can we map all human knowledge and then make connections between non-obvious data points. …

This article explores the significance of data fabrics and knowledge graphs in modern data management. Data fabrics can address the issue of complex, diverse and large-scale data ecosystems that have outgrown traditional centralized approaches. It also outlines the importance of knowledge graphs in bringing a data fabric to your organization. …

The article outlines a pipeline that uses Hugging face Transformers to improve the accuracy of a Knowledge Graph by predicting missing entities and relations while minimising incorrect triples. Before we dive into heavy-duty NLP, it’s important to discuss what knowledge graphs are. …