Modelling learning objects (LO) within their context enables the learner to advance from a basic, remembering-level, learning objective to a higher-order one, i.e., a level with an application- and ...

To stay visible in AI search, your content must be machine-readable. Schema markup and knowledge graphs help you define what your brand is known for.

Tepper School doctoral student Jane JaeYon Pyo developed a novel method using graph theory to measure and interpret the interconnectedness within financial statements, offering a new lens for ...

Meet Graphiti: a Python library for building temporal Knowledge Graphs. Graphiti is designed specifically to manage evolving relationships over time by capturing and recording changes in facts and ...

At the recent Cloud Next conference in Tokyo, Google announced Spanner Graph, a managed feature that integrates graph, relational, search, and AI capabilities within Spanner. This new database ...

Explore the integration of Knowledge Graphs with Large Language Models through Graph RAG. Discover how this innovative approach enhances search capabilities, improves contextual understanding, and ...

The main purpose of this study was to systematically review the graph theory applications for mapping the functional connectivity of the EEG data in neuroergonomics. Moreover, this article proposes a ...

New techniques make graph databases a powerful tool for grounding large language models in private data.

Learn how to build an advanced artificial intelligence (AI) assistant or AI agent using Python and RAG. Provide it with various tools it can ...