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Neuralizing Retrieval: Infusing Symbolic Reasoning into Language Models through Algorithmic Alignment ↗ Retrieval-augmented generation (RAG) has emerged as…

Nature Physics - The strengths of connections in networks of neurons are heavy-tailed, with some neurons connected much more strongly than most. Now a simple network model can explain how this...

This describes the requirements identified for the ontology

By Dr. Verónica Espinoza. 2023

Welcome to Topology, Algebra, and Geometry in Data Science (TAG-DS). This site is intended to bring together researchers who are applying mathematical techniques to the rapidly growing field of data science. The three identified fields encompass more than 100-years of finely tuned machinery that

Trends and recent advancements in Graph and Geometric Deep Learning

Trends and recent advancements in Graph and Geometric Deep Learning

Leveraging Graphs to Advance Chain-of-Thought Reasoning ⛓ Chain-of-thought (CoT) prompting has rapidly emerged as a technique to substantially improve the…

Knowledge Graphs are, IMHO, the best way to structure data for any subsequent analysis. The problem is that the majority of data that is…

The impacts of complexity on the growth and efficiency of big enterprises & how knowledge graphs enable richer insights from data in less time

In my previous post,

Reasoning with Knowledge Graph Clustering in Retrieval-Augmented Generation Systems 🔲 ⚫ Retrieval-augmented generation (RAG) systems have gained immense… | 35 comments on LinkedIn

The secret of AI: it’s all about building your Knowledge Graphs. This open secret deserves more spotlight: a LLM, at its core, is fundamentally a database, a… | 69 comments on LinkedIn

Dive deep into a case study showcasing best practices and pitfalls to avoid, ensuring your journey to a Knowledge Panel is successful.

Find out if using Schema markup increases SEO rankings or correlates with user signals, featuring WordLift experts and adjunct professor Steve Wiideman.

Continuing our exploration of Knowledge Graphs and Ontologies, this next part delves into hands-on implementation. Let’s transform flat CSV…

We’ll delve into the world of ontologies and understand their significance. Additionally, witness the magic of Python as it transforms flat

Injecting KGs in RAG in pre-processing, post-processing, chunk extraction, document and contextual hierarchies, with a concrete example.

Recently there has been much excitement related to Artificial Intelligence and Knowledge Graphs, especially regarding the emerging…

The previous articles of this series, such as Getting Started, have introduced SHACL as a language for representing structural constraints on (knowledge) graphs: classes, attributes, relationships and shapes. These language features describe the formal characteristics that valid instances need to ha

Taxonomies – coherent collections of facts with taxonomic relations – play a crucial and growing role in how we – and AIs – structure and index knowledge. Taken in the context of an "anatomy" of knowledge, taxonomic relations – like instanceOf and subcategoryOf – form the skeleton, a sketchy, incomp

YouTube channel of the COST Action "Distributed Knowledge Graphs" (DKG). We investigate Knowledge Graphs that are published in a decentralised fashion, thus forming a distributed system. COST (European Cooperation in Science and Technology) is a funding agency for research and innovation networks. Our Actions help connect research initiatives across Europe and enable scientists to grow their ideas by sharing them with their peers. This boosts their research, career and innovation. The Action is funded by the Horizon 2020 Framework Programme of the European Union.

Yesterday, I re-shared a huge list of Python visualisation tools - and now, here comes a list of network visualisation tools (these two lists certainly… | 74 comments on LinkedIn

Python open source projects; natural language meets graph technologies; graph topological transformations; graph levels of detail (abstraction layers)

Use Gartner’s impact radar for generative AI to plan investments and strategy with four key themes in mind: ☑️Model-related innovations ☑️Model performance and AI safety ☑️Model build and data-related ☑️AI-enabled applications Explore all 25 technologies and trends: https://www.gartner.com/en/articles/understand-and-exploit-gen-ai-with-gartner-s-new-impact-radar

What do we mean when we say something is a kind of thing? I’ve been wrestling with that question a great deal of late, partly because I think the role of the ontologist transcends the application of knowledge graphs, especially as I’ve watched LLMs and Llamas become a bigger part of the discussion.

This blog post summarizes the findings of our new contribution: