GraphNews

Unlocking graph insights with Raphtory, an advanced in-memory graph tool designed to facilitate efficient exploration of evolving networks. 🔹 Scalability & Performance: Handles large-scale graph data seamlessly, enabling fast computations. 🔹 Temporal Analysis: Investigate how networks change over time, identifying trends and key shifts. 🔹 Multi-layer Modeling: Incorporate diverse data sources into a unified, structured framework for deeper insights. 🔹 Integration: Works easily with existing pipelines via **Python APIs**, ensuring a smooth workflow for professionals. #Graphs #GraphDB #NetworkAnalysis #TemporalData https://www.raphtory.com/

Entity resolution systems face challenges with dense, interconnected graphs, and clique-based graph compression offers an efficient solution by reducing storage overhead and improving system performance during data deletion and reprocessing.

6 years after, where are we? Interested by your feedback concerning the evolution of the graph technologies landscape and about what the current landscape is. https://lnkd.in/eEPkExH | 25 comments on LinkedIn

One of the few things I love as much as Knowledge Graphs (KGs) is basketball (and LEGO bricks, but that’s another story)! So it made…

The best talk during RSA Conference in my mind is: Graphs and Algebras of Defense John Lambert Corporate Vice President, CISO Microsoft What differentiates industry visionary, and average people, is the capability to abstract the theory from practice. John came up with an elegant abstraction of graph “algebra” for cybersecurity defense, that resonates well with my PhD thesis on manifold leanring and graph embedding. The way the algebra operator on cybersecurity graphs is inspiring. I hope more innovations can be sparked by such elegant framework. Leo Meyerovich Alexander Morisse, PhD #GraphThePlanet | 13 comments on LinkedIn

📣 Byte #21: For those of you who want to visualize their graphs inside Jupyter notebooks - we have an exciting development! We recently released an integration with yWorks, who extended their yFiles Jupyter Graphs widget to support Kuzu databases! ✅ Once a Kuzu graph is created, we can instantiate the yFiles Jupyter KuzuGraphWidget, and use the `show_cypher` method to display a subgraph using regular Cypher queries. ✅ There are numerous custom layouts in the yFiles widget (tree, hierarchical, orthogonal, etc.). Give them a try! Here's an example of the tree layout, which is great for visualizing data like this that has rich tree structures. We can see the two-degree mentors of Christian Christiansen, a Nobel prize-winning laureate, in this example. ✅ You can customize the appearance of the nodes in the widget through `add_node_configuration` method. This way, you can display what you're looking for as you iterate through your graph building process. ✅ The Kuzu-yFiles integration is open source and you can begin using it right away for your own interactive visualizations. Give it a try and share around with fellow graph enthusiasts! pip install yfiles-jupyter-graphs-for-kuzu Docs page: https://lnkd.in/g97uSKRe GitHub repo: https://lnkd.in/gjA6ZjiF

To all the knowledge graph enthusiasts who've felt for a while that "graphs are the way to go" when it comes to enabling "intelligence," it was interesting to read Anthropic's "Tracing the thoughts of a large language model" - if you believe that LLMs need graphs to reason, you are right and now you have evidence: Claude answers questions by building and traversing a graph (in latent space) before it translates it back to language: https://lnkd.in/eWFWwfN4 | 20 comments on LinkedIn

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Uncover data's hidden connections using graph analytics in BigQuery. This session shows how to use BigQuery's scalable infrastructure for graph analysis directly in your data warehouse. Identify patterns, connections, and influences for fraud detection, drug discovery, social network analysis, and recommendation engines. Join us to explore the latest innovations in graphs and see real-world examples. Transform your data into actionable insights with BigQuery's powerful graph capabilities.

Learn about different types of graphs and their applications in data management and AI, as well as common misconceptions, in this article by Lulit Tesfaye.

Deep stuff! We uncovered a startling link between #entropy, a bedrock concept in #physics, and how #AI can discover new ideas without stagnating. In an era… | 41 comments on LinkedIn

A graph database that supports more than 100+ billion data, high performance and scalability (Include OLTP Engine & REST-API & Backends) - apache/incubator-hugegraph

Ashley Faith hosted Amy Hodler and me on a recent episode about “2025 Predictions” — here are notes I prepared, to review in 2026…

The Evolution of Intelligent Recommendations with Agentic Graph Systems ➿ Agentic graph systems for recommendation represent a sophisticated fusion of…

Graph is increasingly driving the Agentic space, which I see as being a very good sign. Recently, a programmer asked why graphs would be superior to using…

At Microsoft, we strive to constantly learn and share our insights across innovation, culture and governance. Today, as we reflect on our progress since launching the Secure Future Initiative one year ago, I want to share a little more about our vision for a graph-powered platform future.

As I did my PhD in network and data science, graphs are really close to me. Now, if you would like to get a tast of why these fields are so exciting and…

Causal discovery with panel data? Welcome tigramite Python package. (Note that I am still unsure about causal discovery applications.) I can't find who…

From DAGs to DOGs: Data Object Graph (DOG), queryable, adaptable traversable hybrid data and execution graphs built for AI and traditional analytics use-cases… | 59 comments on LinkedIn

🌐 Unlock the Power of Causal Graphs: Go Beyond Explainability with PyWhy! Hey, #GraphGeeks! Don’t miss Amy Hodler and Michelle Yi’s session at Open Data…

In this series of posts I make an appeal to organize global financial institutions and RiskTech vendors to collaborate on an open-source repository of financial risk patterns called network motifs to…

I work with graphs every day. This simple question left me speechless. During a meeting with a customer I started a sentence saying "In graph theory this… | 28 comments on LinkedIn

If you care about sustainability, I have a data challenge to pull your hair out. What is the path in this supply chain that leads to the least CO2 emissions?…

A curated list of resources for graph-related topics, including graph databases, analytics and science - graphgeeks-lab/awesome-graph-universe

Simplifying Complex Graphs with Nested Nodes and Edges: A Challenge Navigating massive graphs with nested nodes, including groups within groups, can feel like… | 34 comments on LinkedIn

Intelligence analysis utilizing Esri’s analytical, graph, and motion imagery capabilities, all within the same workflow.

Have you wondered about graph theory and how to start exploring it in Python? What resources and Python libraries can you use to experiment and learn more? This week on the show, former co-host David Amos returns to talk about what he's been up to and share his knowledge about graph theory in Python.

Graph-Powered Analytics And Machine Learning With TigerGraph - Driving Business Outcomes with Connected Data

Interactive Network Graphs for Uncovering Complex Multicollinearity 🕸️ Visualize multicollinearity in large datasets with interactive network graphs using… | 18 comments on LinkedIn