The Four Principles of Semantic Parsing
If a parser exists for identifying components within a block of text (a sequence of characters), then that text is structured.
Knowledge graphs are network graphs that link related concepts and properties together to create a form of inferencing engine, with knowledge engineering being the programming aspect of graph usage. Explore how knowledge graphs are created and queried, how they are used as part of a broader form of enterprise metadata management, and how they tie into ML and the IoT.
If a parser exists for identifying components within a block of text (a sequence of characters), then that text is structured.
This is an interview with Dr. Jans Aasman, CEO of Franz, Inc. and designer of the Allegrograph knowledge graph engine. In this interview, we cover everything from the role of Lisp (and Lispers), the versatility of RDF hypergraphs, the value of Allegrograph, and the future of artificial intelligence, machine learning and inferential logic in the graph space.
Webby data architects and modelers–the spider-like ones who use intelligent graph design and a bit of glue or another sticky substance to achieve their objectives–are focused on making joinery much more efficient and scaling a lot more useful with the help of more contextualized data.
Knowledge management is refactoring the way that organizations work.
While Knowledge Graph hype is nowhere near as loud as AI hype, there is no question that more and more organizations are turning to knowledge graphs to solve real-world problems.
For a long time, Gary Marcus was a lonely voice in favour of symbolic(more specifically hybrid) AI models Recent events seem to have emboldened his… Read More »Watching the Shift Towards More Symbolic AGI
An average consumer uses various marketing channels while interacting with a brand. The numbers were calculated in Upland BlueVenn’s latest Digital Divide Report. They examined… Read More »A Single Source of Truth: The 360 Customer View
A century from now, historians will remark on a transformation that seemed subtle at the time but will have huge ramifications over time. Specifically, 2020 will be seen as the year when meetings became transparent.
When XML was first introduced, the W3C XML Working Group took a very unusual step: They created a language for transformations. This effort is now… Read More »The Second Coming of XML
Ontology Hack – Make Use of Existing Enterprise Data Assets Instead of Starting from Scratch As an author of a (reasonably) popular book, I often… Read More »How to Get Started on an Ontology Without Really Trying