Category: Amazon Neptune

Amazon Neptune ML is a machine learning (ML) capability of Amazon Neptune that helps you make accurate and fast predictions on your graph data. Under the hood, Neptune ML uses Graph Neural Networks (GNNs) to simultaneously take advantage of graph structure and node/edge properties to solve the task at hand. Traditional methods either only use […]

Fraudulent activities severely impact many industries, such as e-commerce, social media, and financial services. Frauds could cause a significant loss for businesses and consumers. American consumers reported losing more than $5.8 billion to frauds in 2021, up more than 70% over 2020. Many techniques have been used to detect fraudsters—rule-based filters, anomaly detection, and machine […]

In recent years, social media has become a common means for sharing and consuming news. However, the spread of misinformation and fake news on these platforms has posed a major challenge to the well-being of individuals and societies. Therefore, it is imperative that we develop robust and automated solutions for early detection of fake news […]

Recommendation systems are one of the most widely adopted machine learning (ML) technologies in real-world applications, ranging from social networks to ecommerce platforms. Users of many online systems rely on recommendation systems to make new friendships, discover new music according to suggested music lists, or even make ecommerce purchase decisions based on the recommended products. […]

This post was co-written with Kevin O’Brien, Senior Data Scientist in Careem’s Integrity Team. Dubai-based Careem became the Middle East’s first unicorn when it was acquired by Uber for $3.1 billion in 2019. A pioneer of the region’s ride-hailing economy, Careem is now expanding its services to include mass transportation, delivery, and payments as an […]

This post is co-written by Ian Avilez and Tim Pavlick from HawkEye 360. HawkEye 360 is a commercial radio frequency (RF) constellation, data, and analytics provider. Their signals of interest include very high frequency (VHF) push-to-talk radios, maritime radar systems, Automatic Identification System (AIS) beacons, emergency beacons, and more. The signals of interest library will […]

Medical data is highly contextual and heavily multi-modal, in which each data silo is treated separately. To bridge different data, a knowledge graph-based approach integrates data across domains and helps represent the complex representation of scientific knowledge more naturally. For example, three components of major electronic health records (EHR) are diagnosis codes, primary notes, and […]

For many organizations, consolidating information assets and making them available to employees when needed remains a challenge. Commonly used technology like spreadsheets, relational databases, and NoSQL databases exacerbate this issue by creating more and more unconnected, unstructured data. Knowledge graphs can provide easier access and understanding to this data by organizing this data and capturing […]

Remember the screech of the dial-up and plain-text websites? It was in that era that the Amazon.com website launched in the summer of 1995. Like the rest of the web, Amazon.com has gone through a digital experience makeover that includes slick web controls, rich media, multi-channel support, and intelligent content placement. Nonetheless, there are certain […]