Lovely article Caitlin, a great example of how RDFox can be of real value to the engineering domain

Version 5 is now live…

It’s been a busy few months at Oxford Semantic Technologies, with the launch of our ‘Reasonable Vehicles’ video, growth of our partner network and now, the release of RDFox Version 5!

Along with performance enhancements, the latest version of RDFox brings a variety of new capabilities and updates. RDFox now supports SHACL, property paths and we include a release dedicated to the new Apple M1 ARM chip. These developments mean RDFox now has complete support for SPARQL 1.1. The console has new slick features and our support for OWL and Solr has been updated for increased usability.

“We experienced a…

Trade Surveillance using RDFox

Photo by Nicholas Cappello on Unsplash

When the Food and Drug Administration (FDA) rejected the cancer drug Erbitux in 2001, share price in the pharmaceutical company ImClone dropped significantly. Investors were severely impacted, while those close to Samuel Waksal, the CEO, appeared to benefit. An SEC investigation uncovered that Waksal advised various executives, friends and family to sell their stock, knowing the drug was going to fail the assessments. For this action, Waksal faced seven years in prison and $4.3 million in fines.[1]

Insider trading is a serious offence, punishable with jail time and/or heavy fines. It involves “trading in a public company’s stock by someone…

Artificial Intelligence and Semantic Reasoning

Photo by Jonathan Kemper on Unsplash

Many have strived to make computers ‘think’, ‘learn’ and therefore ‘act’ like humans, all with varying levels of success to date; from machine learning and deep neural networks to knowledge graphs with semantic reasoning.

Artificial intelligence (AI) is the “scientific field of study which aims to understand and build intelligent entities by automating human intellectual tasks”. This trending term is frequently seen in reports, papers, articles and news stories, as interest in AI continues to increase.

There are many parallels between the process of learning in humans, and the work undertaken by computer scientists while creating AI applications. One of…

An on-device context-aware recommendation engine

Photo by Rami Al-zayat on Unsplash

With the increasing popularity of smartphones, personal assistants and applications, comes the need for better on-device recommendation engines.

Recommendation engines are used by many well-known companies such as Amazon, Netflix and Spotify. Currently they tend to be based on four technologies: Collaborative filtering; Content based filtering; Demographic filtering; and Knowledge-based filtering. Each of these models has specific performance weaknesses which often result in poor user rating for relevance.

Mobile phones contain contextual data which could improve recommendation quality; for example, user data in the form of calendars, SMS messages, emails, web search history and app usage logs. …

Creating smart applications for configuration management

Following our earlier blog post on Determining Compatbility, we have teamed up with our partners at metaphacts to create an innovative knowledge graph-based application. The application is built on top of metaphactory, a knowledge graph management, visualisation and interaction platform, and RDFox, our knowledge graph and semantic reasoning engine.

Together, metaphactory and RDFox deliver unprecedented results in compatibility determination scenarios by allowing users to quickly and efficiently gain access to actionable and meaningful insights. This blog will demonstrate the functionality of the metaphactory & RDFox joint solution, using an industrial configuration use case example.

Validate and query large datasets without compromising performance

Photo by C D-X on Unsplash edited by authors

Part One demonstrated how OST Music, a hypothetical music streaming service, was able to link and enrich large datasets of music industry data into a unified knowledge graph.

This article will explain how the same music service was able to validate and query their knowledge graph using RDFox, without compromising speed or correctness.

You can read Part One here.

Validating data

With RDFox, the music platform can validate the music industry data integrated from the various sources. During the data integration process outlined in Part One, inconsistencies can be highlighted, for example, by flagging data which doesn’t corroborate between the three datasets…

Linking and enriching large datasets without compromising performance

Photo by C D-X on Unsplash

The music industry is a dynamic space, with daily new releases, artists, bands and albums. Information on the industry is vast, presenting music platform providers with a great challenge, if their aim is to provide a complete, up to date service for their users.

This two-part article will demonstrate how RDFox can be used within a music streaming service, to link, enrich, validate and query large datasets, with record accuracy and speed. The provider can operate a responsive application, which obtains real value from their data. …

October 2020 marks the release of RDFox Version 4. This comes with several developments, for example, full support for named graphs, full text indexing, performance enhancements, docker containerisation & high availability setup, as well as an improved data explorer. These improvements provide our users with a wider scope for applications of RDFox and we are excited to see what our users do with this feature.

“One of the most important features of Version 4 is the complete support for named graphs. This is important for many of our clients” Founder

RDFox’s functionality has been improved in Version 4 through the…

The Two Strands of Artificial Intelligence

Photo by Maxime VALCARCE on Unsplash

Artificial intelligence (AI) is a widely used term that conjures notions of fantasy, the future, or even threat. This is not surprising considering the multitude of movies which dramatise the role of artificial intelligence and what it may become.

But what is Artificial Intelligence?

In reality, artificial intelligence is a branch of computer science which aims to “understand and build intelligent entities by automating human intellectual tasks”.

These processes have contributed to numerous technological advances across various industries, for example. self-driving cars, technology for diagnosing cancer, revealing fraud in financial services and new data processing techniques. …

Felicity Mulford

Employee at Oxford Semantic Technologies and Ox Mountain. OST have developed RDFox, a high performance knowledge graph and semantic reasoning engine.

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