The O word: do you really need an ontology? The Year of the Graph Newsletter: November / October 2019
How do you manage your enterprise data in order to keep track of it and be able to build and operate useful applications? This is key question all data managements systems are trying to address, and knowledge graphs, graph databases and graph analytics are no different. What is different about knowledge graphs is that they […]
Read More →Graph Algorithms, Neural Networks, and Graph Databases. The Year of the Graph Newsletter, September 2019
One of the world’s top AI venues shows that using graphs to enhance machine learning, and vice versa, is what many sophisticated organizations are doing today. New developments in graph algorithms and analytics, and the latest graph database releases, many of which incorporate graph algorithms and machine learning features. Read the full article on the […]
Read More →Knowledge Graphs and Natural Language Processing. The Year of the Graph Newsletter, July/August 2019
Pinterest gets with the knowledge graph program. Facebook releases a new dataset for conversational Reasoning over Knowledge Graphs. Connected Data London announces its own program, rich in leaders and innovators. And as always, new knowledge graph and graph database releases, research, use cases, and definitions. A double bill summertime newsletter edition, making your knowledge graph […]
Read More →Knowledge Graphs are the new Black. The Year of the Graph Newsletter, May 2019
Knowledge graphs become a centerpiece of Accenture and Microsoft’s toolkits. Knowledge graph lessons from Google, Facebook, eBay, IBM. Graph algorithms and analytics by Neo4j and Nvidia. Connected Data London and JSON-LD goodness, tips and tools for building and visualizing knowledge graphs, using graphs with Elixir and Typescript, and Geometric Deep Learning for a 3D world, […]
Read More →Knowledge graphs, AI, and interoperability. The Year of the Graph Newsletter: February 2019
Knowledge graphs are spreading everywhere: from Airbnb and eBay to Alexa, and from using JSON-LD on the web for better SEO to leveraging taxonomy to define AI. Combining knowledge graphs and machine learning, benchmarking graph databases, and W3C initiative for interoperability shaping up. January 2019 has been a lively month in the graph landscape. Read […]
Read More →More graph databases. The Year of the Graph Newsletter Vol. 8, December 2018
Redis announces RedisGraph and a benchmark, TigerGraph goes AWS, AWS hands-on experiences, new features from Stardog and AnzoGraph, Graphs and Machine Learning, GraphQL, Atlas, DBpedia, Connected Data London and the Year of the Graph. I often get asked about graph databases – what they are, what are they good for, how to choose one, as […]
Read More →Graph gets funding. The Year of the Graph Newsletter Vol. 7, November 2018
October 2018 was the busiest month in the busiest year in graph history, hence the longest Year of the Graph newsletter to date. Neo4j lands a massive funding round, Tinkerpop is moving forward, the most important knowledge graph research event with key industry presence, W3C organizing a Workshop on Web Standardization for Graph Data, and […]
Read More →On Graph query languages. The Year of the Graph Newsletter Vol. 3, June 2018
AWS Neptune goes GA, Microsoft Cosmos DB releases new features, the query language discussion heats up, TigerGraph announces free developer edition, building enterprise knowledge graphs in the real world with Zalando and Textkernel, and more. May has been another interesting month for the graph database world. How can data scientists use knowledge graphs? How, and […]
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