GraphNews

In this blog post, we’re going to walk through designing a graph processing algorithm on top of Neo4j that discovers the influence and sentiment of tweets in your Twitter network.

SERP analysis is an essential step in the process of content optimization to outrank the competition on Google. In this blog post I will share a new way to run SERP analysis using machine learning and a simple python program that you can run on Google Colab. SERP (Search Engine Result Page) analysis is part of keyword research and helps you understand if the query that you identified is relevant for your business goals. More importantly by analyzing how results are organized we can understand how Google is interpreting a specific query. What is the intention of the user making that search?What search intent Google is associating with that particular query?The investigative work required to analyze the top results provide an answer to these questions and guide us to improve (or create) the content that best fit the searcher. While there is an abundance of keyword research tools that provide SERP analysis functionalities, my particular interest lies in understanding the semanti

This post shows how to build serverless GraphQL service by using Azure Functions and GraphQL for .NET.

Given set of SHACL constraints & set of datalog rules, #research detects which constraints could be violated by application of inference rules on some graph instance of the schema, updates original schema to capture new facts #semantics #knowledgegraph http://arxiv.org/abs/1911.00598

Decentralized apps will need a lot of flexibility, which they will gain through data shapes ◆ Ever since Ed Sheeran’s 2017 hit, I just can’t stop thinking about shapes. It’s more than the earworm though: 2017 is the year in which I got deeply involved with Solid, and also when the SHACL recommendation for shapes was published…

With the release of Neo4j 4.0 comes an exciting new feature, called Neo4j Fabric. The operational principle of Neo4j Fabric is in essence quite simple – it provides a way to issue Cypher queries that target more than one Neo4j graph database at once.

As interest grows in new technologies, many enterprises are reconsidering their data warehouses. What makes graph databases different from traditional RDBMSs?

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Recently the Scandinavian banks have once more been showcased in a money laundering case. Unnecessarily so, according to the graph database Neo4j’s founder.

Come to Amsterdam end of June and visit the SIGMOD Workshop on Graph Data Management Experiences & Systems (GRADES) and Network Data Analytics (NDA). #...

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structured data. GNNs have been successfully applied to model systems of relation and interactions in a variety of different domains, including social science, computer vision and graphics, particle physics, chemistry, and medicine. Until recently, most of the research in the field has focused on developing new GNN models and testing them on small graphs

Financial institutions have massive volumes of highly interconnected and structured data, which they need to ingest in real time and to use for a wide range of queries and reports, from simple fund transactions to machine learning-driven fraud detection and risk analysis. To provide a standard format for representing and interchanging such data, the FIBO knowledge graph ontology was developed, to use with triple-store or RDF databases. However, while RDF databases are great for modeling and exchanging data, property graph databases offer a more efficient and intuitive object-oriented approa...

Siren 10.2.3 released! now supercharging #elasticsearch up to v6.8 (7 coming soon) and with @neo4j connectivity (blog post here https://t.co/eIU8t6AjUa) #augmentedanalytics #neo4j #devops #itops #knowledgegraph #investigative pic.twitter.com/xpE4Iq1xG8— Siren (@sirensearch) June 21, 2019

A knowledge graph-based solution helps financial institutions perform efficient and cost-effective media monitoring as part of their KYC processes.

A newbie's guide to querying @Wikidata #opendata #datascience #GraphDB #KnowledgeGraph #tutorial #Neo4j #softwaredevelopment #linkeddata #connecteddata #data #tech @markhneedham @BarrasaDV

My slides for today's talk on Entity Linking: https://t.co/t8iSuTSznG - any feedback, comments & suggestions welcome. Also check out the recent PR which has all of the code for this: https://t.co/YLfevU0OGp #spaCyIRL @spacy_io #NLP— Sofie Van Landeghem (@OxyKodit) July 6, 2019

Solid developer and inrupt advisor on progress with Berners-Lee's vision of re-decentralising the web.

With many thanks to @A_A and @bourgeoa, I’m glad to announce that Solid-IDE and solid-file-client now support file uploads (including binary files like *.mp3, *.png) and selecting multiple files at a time. With Solid-IDE, select the green folder icon next to the name of the folder to hold the uploads, then select “Choose Files”. With solid-file-client in a node.js script, simply call the upload() method (see the README for details). With solid-file-client in a browser script you can can uplo...

GDELT is the largest, most comprehensive, and highest resolution open database of human society ever created. Its vast archives of more than a quarter billion georeferenced records covering the entire world over 30 years, coupled with massive networks that connect all of the people, organizations, locations, themes, and emotions underlying those events, offers unprecedented opportunities to understand and interact with our world in fundamentally new ways.

All organisations find it difficult to fully describe their organisation in data. One of the most common pitfalls is underestimating the number of human-driven connections between data which have never been captured digitally.

This article has two sections. The first describes the longstanding difficulties in integrating data for analytics and more recently, data science and AI.

timers (sourcerers? targeteers?) may recall I originally expected the newsletter to dig into releases and updates to graph technologies. Six months in, I'm finding myself less interested in that and focused more on the intersection between graphs and other topics. I think the result is a newsletter that’s little more compelling than just a record of point releases from graph database vendors.For the graph database vendors reading, ignore the above. I love your point releases and read every single changelog,

More and more #opendata platforms are becoming linked #data. The ONS, @WikiData & Scottish Government all offer SPARQL endpoints to their #linkeddata. SPARQL acts as pattern-matching language @digidatajen @ODcamp #tutorial #knowledgegraph h/t @linkedktk

In social network analysis, a conventional approach relies heavily on available metadata, allowing to match a virtual entity (social network account) to...

Springer Nature and the Knowledge Media Institute (KMi) of The Open University are partnering to provide a comprehensive Computer Science Ontology (CSO) to a broad range of communities engaged with scholarly data. CSO can be accessed free of charge through the CSO Portal, a web application that enables users to download, explore, and provide feedback on the ontology.

A standard query language for property graphs It's official. In June national standards bodies around the world belonging to ISO/IEC's Joint Technical Committee 1 (which is responsible for IT standards) started voting on the GQL project proposal.