We are super excited to share the latest upgrades to ArangoDB which are now available with ArangoDB 3.5. With the fast-growing team, we could build many new and long-awaited features in the open-source edition and Enterprise Edition. Get ArangoDB 3.5 on our download page and see all changes in the Changelog. Need to know more […]

introduction to Knowledge Graph embedding and quick tutorial on Constructing KG via OpenKE package

For more complex products such as new pharmaceutical drugs, medical equipment or healthcare treatments, identifying hubs of influencers among physicians and other healthcare providers requires deep analysis of patient claims data to uncover the referral relationships.

Call records analysis with graph visualization.

How can companies step themselves into the world of graph databases? Neo4j thinks it has an answer. It has been offering a Startup Program for startups with 19 employees or fewer; more than 650 startups with fewer than 20 employees took advantage of having free access to Neo4j Enterprise clusters.

Heritage institutions are places in which works of art, historical records, and other objects of cultural or scientific interest are sheltered and made accessible to the public. The equivalent of that in the digital world, is already taking shape, through digitization and sharing of digital-born or

CSV2RDF 2.0 released! https://t.co/mVvzk2LEXdCSV2RDF is a streaming, transforming, #SPARQL-based #CSV to #RDF converter -now with named arguments (shout-out to @picocli) and a Docker image: https://t.co/Ac1CBFLhgM https://t.co/zyN9DW0qqT— Learning SPARQL (@LearningSPARQL) July 11, 2019

Slides of the LD tutorial at DH2019

Seungwhan Moon, Pararth Shah, Anuj Kumar, Rajen Subba. Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics. 2019.

A knowledge graph connects all data without moving or copying it. A knowledge graph seamlessly layers atop the existing data infrastructure, and reveals the relationships within the data, regardless of its source or format. These graphs are highly scalable, and retain each analysis, which acts as a reusable asset.

Part 1.

From June 2 – 6, I had the pleasure of attending the Extended Semantic Web Conference 2019 held in Portorož, Solvenia. After ESWC, I had another semantic web visit with Axel Polleres, Sabrina…

We are very happy to announce the 0.6 release of the SANSA (Semantic ANalytics StAck) framework - for large-scale analysis, inference, and querying of knowledge graphs! https://t.co/zAFgEaslgU #AI #machinelearning #semanticweb #apachespark #apacheflink #knowledgegraphs— SANSA (@SANSA_Stack) July 2, 2019

Slides for my summer school talk on ML and Embeddings for Knowledge Graphs

How to generate RDF from very large and heterogeneous data sources. Presentation on the Semantiv Big Data workshop @ SIGMOD/PODS 2019 conference.

Modelling knowledge as it *is*, not as it *should be*

The way in which general encyclopaedic knowledge is collected, curated and used has changed dramatically. Anyone in the world can edit Wikipedia at any time, as a registered user or anonymously. This happens in parallel in different languages. To include all even minority languages and avoid a misal

Pinterest is a popular Web application that has over 250 million active users. It is a visual discovery engine for finding ideas for recipes, fashion, weddings, home decoration, and much more. In...

Wikidata is arguably one of Wikipedia's most successful sister projects. It had a profound impact on Wikipedia in just a few years.

In this review, we provide a summary of recent progress in ontology mapping (OM) at a crucial time when biomedical research is under a deluge of an in…

Graph databases such as Neo4J are gaining in popularity. These are in many ways comparable to RDF databases (triplestores), but I will highlight three differences: The underlying datamodel in most …

.@DDIAlliance releases XKOS v1.2 (Extended Knowledge Organization System) specification →facilitates sharing & management of statistical classifications.(For building #Semantic Taxonomies to tag Datasets & #DataScience outputs)https://t.co/HZD1nl5Nu0#BigData #Ontologies #RDF pic.twitter.com/DDYbHqCvm7— Kirk Borne (@KirkDBorne) June 21, 2019

This article, based on a comprehensive history and definitions of the concept, provides a common-sense view of how to understand knowledge graphs.

Combines graph and document technologies, ontology design, and AI data science expertise

Alan Morrison's answer: Graph databases are often used to store knowledge graph data and the accompanying description, predicate and rule-based logic. Knowledge graph: A knowledge graph is a knowledge base that’s made machine readable with the help of logically consistent, linked graphs that tog...

We announce the first release of the knowledge graph for public procurement, integrating tender and company data. TheyBuyForYou is a three year initiative bringing together researchers, innovators and public administrations from 5 European countries. It is supported by EU H2020. The aim of the programme is to make procurement data more easily accessible and hence facilitate better decisions in areas such as economic development, demand management, competitive markets and vendor intelligence.

Artificial Intelligence company Expert System today announced the availability in its Cogito® AI platform of the Creative Works Ontology developed by MovieLabs, the non-profit R&D joint venture started by the major Hollywood studios. MovieLabs’s Creative Works Ontology, published late last year helps fill the need of media companies to adapt their infrastructures to an increasingly … Continue reading "Expert System supports media organizations with the MovieLabs Creative Works Ontology"

When building graph data models we frequently have to deal with a degree of polymorphism for our entities just like the real world. For instance – I’m a person, but I’m also a parent, a spouse, a sibling, a child, a… Implicit categorisation Sometimes the entity categories are entirely defined by relationships to other entities. […]

Read the first installment of this blog series on artificial intelligence on the ways graph technology adds necessary context for powerful AI solutions.