In recent years Knowledge Graphs have been used to solve one of the biggest problems not only in machine learning but also in computer…

The pandemic forced D&A leaders to step up research and analysis to respond effectively to change and uncertainty, the firm says.

This articles introduces the Northwind sample database as a valuable resource to work on development of SPARQL feature proposals.

Topical Authority and Semantic SEO will be discussed more frequently with the concept of Structured Search Engine in the coming years. In this article, you will learn how to use these techniques to grow organic traffic.

Nice machine learning read of the week: E(n) Equivariant Graph Neural Networks. The paper: https://lnkd.in/dfZ3Gh4 Source code: https://lnkd.in/dNfzQRj...

As Enterprise Knowledge Graphs (EKGs) grow, support teams will see an increase in demand for documentation about your graph data.

This blog post will give you an overview of what we have developed in customer projects over the years as our game plan to build a Knowledge Graph-driven, FAIR Data platform and drive digital transformation with data. The post will show you how our product metaphactory can support you every step of the way, and will highlight examples from the life sciences and pharma domains.

Knowledge about entities and their interrelations is a crucial factor of success for tasks like question answering or text summarization. Publicly available knowledge graphs like Wikidata or...

Accurate cardinality estimates are a key ingredient to achieve optimal query plans. For RDF engines, specifically under common knowledge graph processing workloads, the lack of schema, correlated...

This paper introduces a new model to learn graph neural networks equivariant to rotations, translations, reflections and permutations called E(n)-Equivariant Graph Neural Networks (EGNNs). In...

The code property graph (CPG) is a data structure designed to mine large codebases for instances of programming patterns via a domain-specific query language. It was first introduced in the proceedings of the IEEE Security and Privacy conference in 2014 (publication, PDF) in the context of vulnerability discovery in C system code and the Linux kernel in particular.

Selected chapters from my book, A Knowledge Representation Practionary, are now available for free download.

Recent years have seen the growing adoption of non-relational data models for representing diverse, incomplete data. Among these, the RDF graph-based data model has seen ever-broadening adoption,...

Thu, Mar 25, 2021, 9:00 AM: The lack of a convenient way to capture annotations and statements about individual RDF triples has been a long standing issue for RDF. Such annotations are a native featur

We study the problem of adversarially robust self-supervised learning on graphs. In the contrastive learning framework, we introduce a new method that increases the adversarial robustness of the...

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

Really linking them, not doing ETL.

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.

Google's Knowledge Graph algorithm currently updates every 2 to 3 weeks, affecting 60-80% of entities. Here's what SEOs need to know.

The still young discipline of the management and governance of knowledge graphs (KG) is gradually beginning to consolidate on the basis of concrete project ex…

A detailed definition with examples for RDF-Star (also known as “RDF*”), which allows descriptions to be added to edges in a graph.

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

https://lnkd.in/dTvZzMb "A curated list of various semantic web and linked data resources. To add something to the list please either submit a pull request...

A talk about content models, good communications protocols between information and the link between content and graphs.

160 SPARQL endpoints, indexing of stuff in GitHub repositories: interesting work by Vincent Emonet at @UM_IDS: https://t.co/6Jh93YEvRP (file PRs for missing resources here: https://t.co/M5d94NgIrn)— Egon Willighⓐgen (@egonwillighagen) February 27, 2021

2020 Was The “Year of the Knowledge Graph” 2020 was undeniably the “Year of the Knowledge Graph.” 2020 was the year that Gartner put Knowledge Graphs at the peak of its hype cycle. It was the year where 10% of the papers published at EMNLP referenced “knowledge” in their titles. It was the year over […]

In this post i’ll give you an overview of some similarity metrics I’ve discovered when working with WordNet. Even though they were originally proposed as linguistic similarity metrics, …

This article explores the role of knowledge graphs in data fabrics. If you want to learn more about this topic, please join Forrester…