Neo4j unveils cloud graph database for the enterprise

With the general release of Aura Enterprise on Wednesday, Neo4j is offering its first fully-managed cloud graph database designed specifically for large organizations.

The new database is a follow-up for Neo4j, a graph database vendor founded in 2007 and based in San Mateo, Calif. It previously released Aura Professional, a fully managed cloud graph database designed for use by small and medium-sized businesses, in November 2019.

Graph databases enable users to access and use their data in different ways than traditional relational databases. They simplify the connection of data points, allowing them to simultaneously connect with more than one other data point in order to more quickly pull data from disparate sources and speed up the process of turning data into insights.

Common use cases include fraud detection, social networking and generating recommendations.

The new technology

Aura Enterprise is designed to enable organizations to build graph applications at enterprise scale, advancing the capabilities of Aura Professional, which empowered small- and medium-sized business to build their applications. It facilitates the management of large data sets with billions of nodes and relationships for fast data queries, and provides enterprise-grade security with end-to-end encryption and node-level access controls.

As with Aura

Supercomputer HPE-Cray EX to Rank Among World’s Fastest; Will Help Study Climate Change, Wildfires, More

A new supercomputer in Wyoming will rank among the world’s fastest and help study phenomena including climate change, severe weather, wildfires and solar flares.

Houston-based Hewlett Packard Enterprise won a bid to provide the $35 million (roughly Rs. 255 crores) to $40 million (roughly Rs. 300 crores) machine for a supercomputing centre in Cheyenne, the National Center for Atmospheric Research in Boulder, Colorado, announced Wednesday.

The HPE-Cray EX supercomputer will theoretically be able to perform almost 20 quadrillion calculations per second — 3.5 times faster than the existing machine at the NCAR-Wyoming Supercomputing Center.

The new machine’s maximum speed per second will be roughly equivalent to each person on Earth completing a math equation every second for an entire month.

That power will enable some of the most sophisticated simulations yet of large-scale natural and human-influenced events.

The supercomputer should rank among the world’s 25 fastest after it’s installed this year and goes into operation in early 2022, according to the National Center for Atmospheric Research.

It “will support basic research in ways that will lead to more detailed and useful predictions of the world around us, thereby helping to make our society more resilient to increasingly costly disasters and

Privacy Information Classification: A Hybrid Approach

Social networks provide convenience for users but pose some risks at the same time. While publishing information online, users can accidentally disclose personal information, such as email address, hometown, or activities attended. A tool which would automatically detect personal information and reminding user would be hence useful.

Illustration by Rami Al-zayat on Unsplash, free licence

Recently, a group of researchers proposed an extended version of their older privacy leakage detection framework. It combines both deep learning and ontology models. The deep learning model detects the privacy leakage on online social data.

The ontology privacy model is developed from massive data collected from real-world social networks and classifies the information into nine subtypes. Therefore, not only users are reminded that they are going to post sensitive information but also notified what the kind of private data is concerned. It may help the user to avoid repeating the mistake again.

A large amount of information has been published to online social networks every day. Individual privacy-related information is also possibly disclosed unconsciously by the end-users. Identifying privacy-related data and protecting the online social network users from privacy leakage turn out to be significant. Under such a motivation, this study aims to propose

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At the time I was writing my latest hub, and with all the discuss individuals not reading lengthy articles on cell devices, I was a bit perturbed that I couldn’t seem to shorten it and nonetheless tell the story I wanted to inform. After my revelation with the WaPo article, I happily wrote what the hub wanted to say, …