GraphNews

Apollo's new platform, Supergraph, is a collection of tools that can work together to generate reports, dashboards and general answers.

Co-authors: Joshua Shinavier and Shirshanka Das

Co-authored by Abhishek Singh, Machine Learning Engineer at Bayer Pharmaceuticals, former Microsoft, JPMorgan Chase & Co, HSBC, and by…

🔥 Attention Guided Graph Convolutional Networks for Relation Extraction 🔥 Code: https://bit.ly/3KdGOKy Graph: https://bit.ly/3FJMRmN...

Last week I had the pleasure and privilege of attending the 4th annual Knowledge Graph Conference (KGC) at Cornell Tech in NYC. In addition to contributing my own talk on “Boutique Knowledge Graphs” and participating in a panel on “Content Knowledge Graphs,” I attended two days of inspiring and insi

Logseq is pitching a privacy-focused open-source platform that helps people manage and collaborate around their knowledge bases.

ISI's Center on Knowledge Graphs research group combines artificial intelligence, the semantic web, and database integration techniques to solve complex information integration problems

"Graph Neural Networks (GNNs) are not limited to classifying nodes. One of the most popular applications is graph classification. This is a common task...

Creates the first relational knowledge graph system; adds Bob Muglia to its board

Topic Modelling: A primer and A mental model. After Philip Vollet’s post on Top2Vec, many of you pinged. So here you go. 👉 Criteria A: Discover topics... 15 comments on LinkedIn

Deep Narrative Analysis' (DNA's) long-term goals will be achieved by research and experimentation, taking small steps and refining our desig...

[🥳new video🧠] You thought that the curvature of space and Ricci flow (famously used by Grisha Perelman to solve a 1.000.000$ millennium problem (Poincaré...

New GraphML explanation video is up! 🎉 Derek Lim and Joshua Robinson explain their Sign- and Basis- invariant graph positional encoding. The future of...

Knowledge graphs (KGs) have emerged as a compelling abstraction for organizing the world's structured knowledge and for integrating information extracted from multiple data sources. They are also beg...

We are delighted to share that our #gnn tutorial has been accepted by #IJCAI2022 joint with Prof. Jian Pei, Prof. Peng Cui, Prof. Liang Zhao, Dr. Xiaojie...

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To overcome such inherent challenges with graph neural networks and improve recommendation abilities, LinkedIn has created a process it calls Performance-Adaptive Sampling Strategy (PASS). that uses AI to select the neighbors in graphs that are the most relevant, thus improving predictive accuracy.

By Alex Hutter, Falguni Jhaveri and Senthil Sayeebaba

The Studio Search platform takes a portion of the federated graph and makes it searchable.

Knowledge graphs (KGs) are a novel paradigm for the representation, retrieval, and integration of data from highly heterogeneous sources. Within just a few years, KGs and their supporting technologie...

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This week, enterprise data catalog provider data.world announced both a $50 million Series C round and a new suite of data catalog management capabilities

Information extraction, drug discovery, and software analysis are just a few applications of this versatile tool.

The complexity of cancer research stems from leaning on several biomedical disciplines for relevant sources of data, many of which are complex in their own right. A holistic view of cancer—which is critical for precision medicine approaches—hinges on integrating a variety of heterogeneous data sources under a cohesive knowledge model, a role which biomedical ontologies can fill. This study reviews the application of ontologies and knowledge graphs in cancer research. In total, our review encompasses 141 published works, which we categorized under 14 hierarchical categories according to their usage of ontologies and knowledge graphs. We also review the most commonly used ontologies and newly developed ones. Our review highlights the growing traction of ontologies in biomedical research in general, and cancer research in particular. Ontologies enable data accessibility, interoperability and integration, support data analysis, facilitate data interpretation and data mining, and more recently, with the emergence of the knowledge graph paradigm, support the application of Artificial Intelligence methods to unlock new knowledge from a holistic view of the available large volumes of heterogeneous data.

Knowledge graphs, the technology powering Google, Facebook and Apple, is now unlocking value across the financial sector. Knowledge graphs are transforming critical capabilities and enterprises are increasingly looking to the technology to enhance their tax strategy, perform compliance and improve customer service.

A new generation of note-taking tools helps us quickly organize thoughts as knowledge graphs

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