Category Archives: Semantic Web

Knowledge Specification and Querying

Our colleagues from the Rules and Reasoning community have just reported interesting results. They built a system that achieves 100% accuracy on an extensive test suite of movie-related questions, e.g. “Who appears in a Steven Spielberg directed film?”. Their approach … Continue reading

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“Rules and Reasoning” Event at W3C Graph Data Workshop

This event was held on March 4-6, 2019 in Berlin, Germany.  The following kinds of rules were discussed: Rules for graph knowledge inference Rules for graph data transformation/mapping Rules for graph data validation Rules for RDF shapes Rules for (controlled) natural … Continue reading

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Tim Berners-Lee: Game On!

With an ambitious decentralized platform, the father of the web  Sir Tim Berners-Lee will launch Inrupt, a startup that he has been building, in stealth mode, for the past nine months. Its mission is to turbocharge a broader movement afoot, among … Continue reading

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Will we see Prolog’s resurgence?

Is Prolog the next good idea? Prolog, introduced in 1972, “was a short introduction to open doors to other languages than C, Java, Python or so. In a jungle of hundreds of programming languages, Prolog fits like a glove into the formalism of … Continue reading

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Knowledge Graphs

Knowledge Graphs are becoming increasingly important to support decision and process augmentation based on linked data. “It’s all about things, not strings: A Knowledge Graph represents a knowledge domain. It connects things of different types in a systematic way. Knowledge … Continue reading

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Smart Snippets: Semantic Web Comes of Age

On Aug. 3 Forbes published an article “The Semantic Web Comes of Age” by Kurt Cagle. “Beginning in 2017, both Google and Bing announced that they would be supporting the use of embedded smart snippets in web content. A smart snippet is a … Continue reading

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NYT Interview with Benjamin Grosof

New Your Times published an interview with Benjamin Grosof, a leading AI expert and a frequent presenter at RuleML+RR and DecisionCAMP.  While deep learning comes from the statistical side of AI, the interview brings attention to non-deep learning tools such as Prolog, a programming language … Continue reading

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