Financial fraud is growing and it is a costly problem, estimated at 6% of the Global Domestic Product, more than $5 trillion in 2019.

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

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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

Learn advanced Cypher queries for one approach to analyzing data inconsistencies directly in your flexible and forgiving Neo4j graph database.

Feeling SHACL'd to your desk at home these days? Then try out SHACL Play!, a "free online SHACL validator for RDF data" from Thomas Francart bit.ly/2QfpbQ5

"This article presents our ontology – that is, how we express mathematical ideas and relationships in the Cambridge Mathematics Framework – with examples from the CM Framework itself." twitter.com/CambridgeMaths…

thanks for making them available Ruben! twitter.com/RubenVerborgh/…

making, effectiveness and competitive edge.

Graph databases and analytics are getting ever more accessible and relevant

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In 2019, I was asked to write the Foreword for the book “Graph Algorithms: Practical Examples in Apache Spark and Neo4j“, by Mark Needham and Amy E. Hodler. I wrote an extensive piece on the power of graph databases, linked data, graph algorithms, and various significant graph analytics applications. In their wisdom, the editors of the book decided that I wrote “too much”. So, they correctly shortened my contribution by about half in the final published version of my Foreword for the book.

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semanti… https://t.co/d0FvOQ2HlK

Michael Bolle of Bosch.

Accelerated Graph Computing Framework in C++" drum.lib.umd.edu/handle/1903/21… see Gremlin++ code here: github.com/bgamer50/Greml… #graphdb https://t.co/LmSsABE7SW

enterprise context, the problem arises of managing information sources that do not use the same technology, do not have the same data representation, or that have not been designed according to the same approach. Thus, in general, gathering information is a hard task, and one of the main reasons is that data sources are designed to support specific applications. Very often their structure are unknown to the large part of users. Moreover, the stored data is often redundant, mixed with information only needed to support enterprise processes, and incomplete with respect to the business domain. Collecting, integrating, reconciling and efficiently extracting information from heterogeneous and autonomous data sources is regarded as a major challenge. Over the years, several data integration solutions have been proposed:

"name": "Sherman McCoy",

* SketchGCN: Semantic Sketch Segmentation with Graph Convolutional Networks (arxiv.org/abs/2003.00678)

“Aspen is a simple markup language for creating graph data.”

And Find out who are the most Influencers in Game of ThronesContinue reading on Towards Data Science »

A mathematical theory is presented for the representation of knowledge in the

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Cf. this discussion on the #schema.org mailing list kicked off by this post's author lists.w3.org/Archives/Publi…

Introducing the Neo4j Graph Data Science plugin with examples from the “Graph Algorithms: Practical Examples in Apache Spark and Neo4j” bookIn the past couple of years, the field of data science has gained much traction. It has become an essential part of business and academic research. Combined with the increasing popularity of graphs and graph databases, folks at Neo4j decided to release a Graph Data Science (GDS) plugin. It is the successor of the Graph Algorithms plugin, that is to be deprecated.Those of you who are familiar with Graph Algorithms plugin will notice that the syntax hasn’t changed much to allow for a smoother transition. To show what has changed, I have prepared the migration guides in the form of Apache Zeppelin notebooks that can be found on GitHub.Neo4j connector for Apache Zeppelin was developed by Andrea Santurbano, who also designed the beautiful home page notebook of this project and helped with his ideas. In the migrations guides, we used the ex

here's what's new in 20c: blogs.oracle.com/oraclespatial/… #oraclegraph #Analytics #DataScience https://t.co/hXlgPgxcxJ

https://t.co/4Ohse28toR

To help promoting the usage of @wikidata , here's another attempt to explain properties of statements with one of the most used qualifiers "start time" (pq:P850).Try it: https://t.co/tvOeWK7qBM#SPARQL #LinkedData pic.twitter.com/RshdPRx92D— Ivo Velitchkov (@kvistgaard) February 20, 2020

Very nice article highlighting recent proof that complete graphs can be decomposed into smaller multiple trees. twitter.com/QuantaMagazine…