Read this interview with Ivan Zoratti – the former Chief Technology Officer of MariaDB – and learn why he joined Neo4j as the Director of Product Management.

Today we want to make this available in a first release under an Apache License for you to try out and test. It works with Neo4j from 3.4.x

This survey provides #knowledgegraph review: KG representation learning, knowledge acquisition & completion, temporal KG, KG #applications. It summarizes recent breakthroughs & perspective directions to facilitate future #research #AI #data h/t @aaranged

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

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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...

Analyzing US Lobbying Data in #Neo4J #graphdatabase

https://t.co/7T0EOs6yG7 - Made this tiny tool to discover related subreddits.The graph is created based on jaccard similarity between two subreddits. Jaccard similarity is constructed from set of shared users.Source code https://t.co/J9r1jl1JjR pic.twitter.com/4hcg7mI4sg— Andrei Kashcha (@anvaka) January 10, 2019

.@CamSemantics announces Anzo #GraphDB v.2: RDF*, Custom SDK, Free Edition. "Imagine being able to do labeled properties, just like you do in Neo4j & other property graphs, but also have capability of RDF to help w ontologies & inferencing" #data #tech

powered applications with minimum friction.Broad compatibility with existing and future software developm

grade features and scale. We appreciate your candid stories and collaboration, and we’ve used this to create a better solution. As such, we’re excited to announce Neo4j for Graph Data Science™, the first data science environment built to harness the predictive power of relationships for enterprise deployments. Neo4j for Graph Data Science is an ecosystem of tools that includes: With Neo4j for Graph Data Science, data scientists are empowered to confide

Personally, I am always most excited by technology when it can have a positive impact on society and the lives of ordinary people. Curing…

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 […]

Augmented analytics tools, NLP search and graph analytics are the top trends for 2019 and beyond. Experts say augmented analytics and NLP are transforming how enterprises consume data and derive in...

We're excited to announce the public release of Akutan, a distributed knowledge graph store, under the Apache 2.0 open source license. Akutan is the result of four person-years of exploration and engineering effort, so there's a lot to unpack here! This post will discuss what Akutan is, how it's implemented, and why we've chosen to release it as open source.

MP voting records are public record in the UK, detailed #data is available about how each MP has voted in each bill @PublicWhip collect data & make it accessible @joshua_e_k explores how to use a #GraphDatabase to look at MP’s voting record similarity

2 together with its impact on human health. One aspect of this is organizing existing and emerging information about viral and host cell molecular biology, disease epidemiology, phenotypic progression, and effect of drugs and other treatments in individuals.

It seems like every crime show includes a few scenes where we see that the detective has built a wall of pictures, newspaper clippings, index cards and other interesting documents, linking all these things together through a network of string and push pins. This linked data allows them to step back and see how the facts relate and helps provide the bigger picture of what happened and how to solve it. Seeing the bigger picture allows detectives to use inductive and deductive reasoning to pursue leads,identify gaps in their knowledge and continue the investigation in ways they may not have seen before.The crime wall is a physical representation of knowledge or context. The crime wall helps investigators see the relationships and understand the true meaning of the facts surrounding a case. Understanding context can lead to accelerated insights and increase the productivity of the detectives. In the digital world, we can represent knowledge through similar techniques. We call this di

Leveraging the Neo4j Community Graph For Social Discovery

My new paper on ontologies in Data and SW engineering https://t.co/jqQAEMZbEl @nimonika— Christian Dirschl (@HaintzD) January 3, 2019

answering service — among other things.Expanding a knowledge graph often involves integrating it with another knowledge graph. But different graphs may use different terms for the same entities, which can lead to errors and inconsistencies during integration. Hence the need for automated techniques of entity alignment, or determining which elements of different graphs refer to the same entities.In a paper accepted to the Web Conference, my colleagues and I describe a new entity alignment technique that factors in information about the graph in the vicinity of the entity name. In tests involving the in

Analysing Load and Query Times across DBPedia and Yago

Creating Graphs in Python using Networkx #dataviz #tutorial #datascience #data #tech

Knowledge graphs have emerged as a compelling abstraction for organizing world's structured knowledge over the internet, capturing relationships among key entities of interest to enterprises, and a way to integrate information extracted from multiple data sources. Knowledge graphs have also started to play a central role in machine learning and natural language processing as a method to incorporate world knowledge, as a target knowledge representation for extracted knowledge, and for explaining what is being learned. This class is a graduate level research seminar featuring prominent researchers and industry practitioners working on different aspects of knowledge graphs. It will showcase how latest research in AI, database systems and HCI is coming together in integrated intelligent systems centered around knowledge graphs.The seminar will be offered over Zoom as per the planned schedule.The seminar is open to public. Remote participants may join the seminar through Zoom. To be

In this post I explain common issues with query performance in Neo4j and how you may solve them using the Query Log Analyser tool.

Increasingly complex products undoubtedly require greater management of components, function and data. Classic product data management (PDM) has long reach its limits in this respect. Breaking down product DNA is now driven by artificial intelligence (AI) and knowledge graphs. In… Read more →

Discover tips and strategies for implementing graph embedding into a Neo4j graph database, with plenty of Cypher examples.