Graph Algorithms in Neo4j: Closeness Centrality

Graph algorithms provide the means to understand, model and predict complicated dynamics such as the flow of resources or information, the pathways through which contagions or network failures spread, and the influences on and resiliency of groups. This blog series… Read more →

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#GraphCast: Fake News Edition

Welcome to this week’s #GraphCast – our new series featuring what you might have missed on the Neo4j YouTube channel. Last time, our Editor-in-Chief, Bryce Merkl Sasaki, pivoted away from video and onto the podcast medium to highlight a recent… Read more →

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Graph Algorithms in Neo4j: Degree Centrality

Graph algorithms provide the means to understand, model and predict complicated dynamics such as the flow of resources or information, the pathways through which contagions or network failures spread, and the influences on and resiliency of groups. This blog series… Read more →

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Social Power, Operational Ease: 5-Minute Interview with David Fox, Software Engineer at Adobe

“We were able to go from 48 Cassandra instances to three Neo4j instances. Going into the project, we weren’t sure whether that was going to be possible,” said David Fox, Software Engineer at Adobe. Adobe runs Behance, a social network… Read more →

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The Top 10 Neo4j Podcasts of 2018

Since March 2015, Neo4j VP Rik Van Bruggen has been hosting the Graphistania podcast, covering the wonderful world of graph database technology and interviewing some of the most interesting graph thinkers and developers from across the globe. If you’re new… Read more →

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Graph Databases for Beginners: Native vs. Non-Native Graph Technology

It’s a common figure of speech: “Jack of all trades, master of none.” The heart behind the phrase is that if you’re trying to be good at everything, you normally end up being sort of mediocre at a large number… Read more →

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Fraud Detection Using Graph Technology

Graph technology refers to the storage, management and querying of data graphical representation. Here, your indices become vertices and your relationships are converted into edges. Through analysis of the fine-grained relationships, by using graph analysis, you can find out oddities… Read more →

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How Real-Time Recommendations Increase Revenues, Optimize Margins and Delight Customers [Infographic]

“You may also like” sounds simple, but there’s a lot happening behind the scenes. Real-time recommendations work best when they take into account both the user’s needs (what is of interest to them) and your business strategy (items you need… Read more →

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Graph Algorithms in Neo4j: Use Cases for Graph Transactions & Analytics

Today’s most pressing data challenges center around connections, not just tabulating discrete data. Graph analytics accelerate breakthroughs across industries with more intelligent solutions. This blog series is designed to help you better leverage graph analytics so you can effectively innovate… Read more →

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Graph Databases for Beginners: Graph Theory & Predictive Modeling

There’s a common one-liner, “I hate math…but I love counting money.” Except for total and complete nerds, a lot of people didn’t like mathematics while growing up. In fact, of all school subjects, it’s the most consistently derided in pop… Read more →

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Powering Recommendations with a Graph Database: Connect Buyer and Product Data

Effective recommendations increase revenue and drive up average order value. But delivering highly relevant, real-time recommendations requires as much context as possible. Connecting the user to the perfect recommendation is an art. In this three-part series, we explore using recommendations… Read more →

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Graph Databases for Beginners: Data Modeling Pitfalls to Avoid

With the advent of graph database technology, data modeling has become accessible to masses. Mapping business needs into a well-defined structure for data storage and organization has made a sortie du temple (of sorts) from the realm of the well-educated… Read more →

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Knowledge Graphs: The Path to Enterprise AI

Editor’s Note: This presentation was given by Michael Moore and Omar Azhar at GraphConnect New York in October 2017. Presentation Summary Once your data is connected in a graph, it’s easy to leverage it as a knowledge graph. To create… Read more →

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Visualizing Healthy Lifestyles: 5-Minute Interview with Alicia Powers, SVP at NYCEDC

“The future of graph technology is already here. It’s everywhere, because we can model anything in a way that’s more close to how it is in real life,” said Alicia Powers, Senior Vice President at New York City Economic Development… Read more →

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Graph Algorithms in Neo4j:
15 Different Graph Algorithms & What They Do

Graph analytics have value only if you have the skills to use them and if they can quickly provide the insights you need. Therefore, the best graph algorithms are easy to use, fast to execute and produce powerful results. Neo4j… Read more →

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Neo4j as a Critical Aspect of Human Capital Management (HCM)

Editor’s Note: This presentation was given by Luanne Misquitta at GraphConnect Europe in May 2017. Presentation Summary In this presentation, Luanne Misquitta shares her facility for engaging with the challenges of human capital management (HCM) in contemporary organizations using graph… Read more →

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The Story behind Russian Twitter Trolls: How They Got Away with Looking Human – and How to Catch Them in the Future

It’s no secret that Russian operatives used Twitter and other social media platforms in attempt to influence the most recent U.S. presidential election cycle with fake news. The question most people aren’t asking is: How did they do it? More… Read more →

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Neo4j: A Reasonable RDF Graph Database & Reasoning Engine [Community Post]

[As community content, this post reflects the views and opinions of the particular author and does not necessarily reflect the official stance of Neo4j.] It is widely known that Neo4j is able to load and write RDF. Until now, RDF… Read more →

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Network Science: The Hidden Field behind Machine Learning, Economics and Genetics That You’ve (Probably) Never Heard of – An Interview with Dr. Aaron Clauset [Part 2]

Last week, in part one of my interview with Dr. Aaron Clauset, we reviewed how network science was evolving and how it’s dismantling preconceived notions about networks in general. Clauset also stressed the crucial role of interdisciplinary collaboration when it… Read more →

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Network Science: The Hidden Field behind Machine Learning, Economics and Genetics That You’ve (Probably) Never Heard of – An Interview with Dr. Aaron Clauset [Part 1]

I recently had the opportunity to combine work and pleasure and meet with Dr. Aaron Clauset, an expert on network science, data science and complex systems. In 2016, Clauset won the Erdos-Renyi Prize in Network Science but you might be… Read more →

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The ICIJ Releases Neo4j Desktop Download of Paradise Papers

Early this morning (1 Dec.), the Pulitzer Prize-winning International Consortium for Investigative Journalists (ICIJ) released an ICIJ version of Neo4j Desktop which includes the Paradise Papers and the other Offshore Leaks graph data. This desktop package – available for Windows,… Read more →

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Analyzing the Paradise Papers with Neo4j: A Closer Look at Queries, Data Models & More

Our friends from the ICIJ (International Consortium of Investigative Journalists) just announced the Paradise Papers this past week, a new trove of leaked documents from the law firm Appleby and trust company Asiaciti. Similar to the Panama Papers before (which… Read more →

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Neo4j: The Power behind the Paradise Papers

Once again, the International Consortium of Investigative Journalists (ICIJ) has shaken the world with a far-reaching, in-depth investigation into the shadowy world of offshore finance: The Paradise Papers. Using Neo4j, the ICIJ has built upon their Pulitzer Prize-winning investigation of… Read more →

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Going Meta: Exploring the Neo4j Graph Database…as a Graph

The graph data model is inherently visual. Try explaining a graph to someone new. You’ll inevitably draw a picture, or wave your hands around to convey what you mean by ‘nodes… links…. and more nodes’. People think in graphs, and… Read more →

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Analyzing Twitter Hashtag Impact using Neo4j, Python & JavaScript

This is the first demo I developed with Neo4j. The objective of the demo is to open the discussion about graph databases, Neo4j, big data, analytics and IBM Power Systems with our global customers. I decided to use Twitter as… Read more →

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