Firms that fail to shine light on their dark data risk ceding the high ground in insights and inviting risk exposures lurking ...

Data-hungry AI applications are fed complex information, and that's where graph databases and knowledge graphs play a crucial role.

Neo4j has introduced "property sharding" which, according to one analyst, will help overcome its earlier struggles with ...

The enterprise knowledge graph is a knowledge representation system based on graph structures. It integrates multi-source data from both internal and external sources (such as business information, ...

Recorded content, as an important carrier of learning scenarios, is no longer just a simple "classroom replay." To truly serve learning needs, the core lies in mining structured knowledge from vast ...

With agentic AI serving as a coach, employees can gain the kind of personalized learning that ensures success and keeps ...

How your behavior affects your financial health, and learn ways to improve it for better finances by understanding behavioral ...

Context, not content, now drives AI visibility, making structured data the strategic data layer every enterprise must ...

Google’s Knowledge Graph saw its largest contraction in a decade in June: a two-stage, one-week drop of 6.26% – over 3 billion entities deleted. Since 2015, we’ve tracked the Knowledge Graph and have ...

A study led by Jun Cheng from Xiamen University and collaborators introduces a new workflow for recommending relay catalysis pathways. The workflow uses large language models (LLMs) to extract and ...