Overview of the research domain and works of the joint research team Wimmics (UCS, Inria, CNRS, I3S) in Sophia Antipolis, France

Knowledge graphs are used in various applications and have been widely analyzed. A question that is not very well researched is: what is the price of their pro…

The original Semantic Web vision foresees to describe entities in a way that the meaning can be interpreted both by machines and humans. Following that idea, l…

Stardog 5.1 adds support for GraphQL, an expressive path query SPARQL extension, and stored functions.

Learn how to find similar items in the Knowledge Graph with machine learning.

A knowledge graph is the only realistic way to manage enterprise data in full generality, at scale, in a world where connectedness is everything.

by Dr. Xu Yu, CEO and Dr. Victor Lee, Director of Product Management [Excerpted from the eBook Native Parallel Graphs: The Next Generation of Graph Database for Real-Time Deep Link Analytics] Until recently, graph database designs fulfilled some but not all of the graph analytics...

Recently RedisGraph published a blog [1], comparing their performance to that of TigerGraph’s, following the tests [2] in TigerGraph’s benchmark report [3], which requires solid performance on 3-hop, 6-hop, and even 10-hop queries. Multi-hop queries on large data sets are the future of graph analytics....

literally as well as figuratively (through investments, supplying

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Read about why and how knowledge graph technology helps build networks of interwoven digital objects in the world of cultural heritage.

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Don't try to put the cart before the horse: realize that efficient data preparation (and thus interoperable standards) and data quality, especially in the enterprise environment, are a basic requirement for all applications of artificial intelligence. The development of competences and experts in th

We are going to show how we import the W3C Organizational Ontology into Neo4j using the neosematics tools.

Five diverse technology companies show how it's done.

After more than a decade, the supply-driven approach to publishing public (open) data has resulted in an ever-growing number of data silos. Hundreds of thousands of datasets have been catalogued and can be accessed at data portals at different administrative levels. However, usually, users do not think in terms of datasets when they search for information. Instead, they are interested in information that is most likely scattered across several datasets. In the world of proprietary in-company data, organizations invest heavily in connecting data in knowledge graphs and/or store data in data ...

Virtual assistants do their jobs better thanks to Wikidata, which aims to (eventually) represent everything in the universe in a way computers can understand.

Part 3 in a series about Knowledge Graphs

To understand trends as they’re happening, @pinteresteng needs to understand content & categories. To do that, they built a taxonomy-based knowledge management system that enables content understanding in a highly efficient way #knowledgegraph #AI #data

Song Cui and Dhananjay Shrouty | Software Engineers, Content KnowledgeInterest Taxonomy at PinterestWe recently began rolling out the beta version of Pinterest Trends, a new tool that gives a view...

Bill Slawski is an SEO legend.

Interview with Oshani Seneviratne – Healthier eating for diabetics with the RPI + IBM Food KG Interview – RPI Food KG with Oshani Seneviratne Tell us about your project. The food knowledge graph (or foodkg) is a joint project between Rensselaer Polytechnic Institute and IBM (part of the IBM AI Horizons Network). The project’s official […]

After building and selling Heyzap back in 2016 I had free reign to dig into the question of “what should I really be working on?” and how to create something that would have a lasting impact on society. In part of this journey I’ve had the privilege to invest

Until now the only way to run Graph Algorithms on Neo4j has been to learn Cypher. The Graph Algorithms Playground changes all that.

#KnowledgeGraphs & #Applications. What makes a KG what it is, is that, unlike a regular database that gets populated & stays dormant, a KG is supposed to re-purpose itself, provide new insights and inferences #datascience #AI #analytics @AnalyticsVidhya

Introduces core concepts of Linked Open Data, including URIs, ontologies, RDF formats, and a gentle intro to the graph query language SPARQL.

SPARQL 1.2 Community Group. Contribute to w3c/sparql-12 development by creating an account on GitHub.

On the Role of #KnowledgeGraphs in Explainable #AI: A #MachineLearning Perspective @freddylecue @Inria h/t @aaranged @iswc_conf #iswc2019 #semex2019 #research http://www-sop.inria.fr/members/Freddy.Lecue/presentation/ISWC2019-FreddyLecue-Thales-OnTheRoleOfKnowledgeGraphsInExplainableAI.pdf