BestHub
Sign in
Tagged articles

semantic governance

8 articles · Page 1 of 1
AI Large-Model Wave and Transformation Guide
AI Large-Model Wave and Transformation Guide
Oct 29, 2026 · Artificial Intelligence

qOntology vs OntoL: Modeling Workbench vs Reasoning Engine – Complete Comparison

This article compares qOntology, an open-source ontology modeling and semantic governance workbench focused on TBox design and collaboration, with OntoL, a closed-source runtime reasoning engine featuring a custom reasoner for TBox+ABox inference, SHACL validation, and industrial event-driven reasoning, showing how they complement each other in a combined pipeline.

ABoxIndustrial IoTOntology
0 likes · 12 min read
qOntology vs OntoL: Modeling Workbench vs Reasoning Engine – Complete Comparison
DataFunSummit
DataFunSummit
Sep 29, 2026 · Artificial Intelligence

From 50% to 95%: Amap's 4-Talk Blueprint for Trustworthy Decision Agents

Amap shares four conference talks detailing how they built trustworthy AI agents for business decisions, covering semantic governance, causal evaluation, evaluation-driven development, and a product architecture shift that lifted accuracy from 50% to 95% by separating deterministic computation from model reasoning.

AI agentsAmapBusiness Analytics
0 likes · 21 min read
From 50% to 95%: Amap's 4-Talk Blueprint for Trustworthy Decision Agents
AI Large-Model Wave and Transformation Guide
AI Large-Model Wave and Transformation Guide
Sep 1, 2026 · Artificial Intelligence

Why Ontology‑Based Semantic Governance Is the Decisive Factor for Enterprise Large‑Model Deployment

Enterprises adopting large language models often face hallucinations across systems due to inconsistent semantics, and the article explains how ontology‑driven semantic governance provides a unified semantic infrastructure that enables single‑system control, cross‑system decision making, and advanced regulatory reasoning, ultimately turning a large model into a shared enterprise semantic brain.

Enterprise AIOntologydigital twin
0 likes · 11 min read
Why Ontology‑Based Semantic Governance Is the Decisive Factor for Enterprise Large‑Model Deployment
Data Bricklaying Diary
Data Bricklaying Diary
Aug 17, 2026 · Artificial Intelligence

Don't Overhype Ontology: A Three-Gate Framework for AI Semantic Decisions

This article warns against treating ontology as a universal solution for AI scenarios, distinguishing semantic governance, deterministic computation, and dynamic reasoning, and provides a three-gate decision framework to evaluate when ontology adds value versus when simpler mechanisms suffice.

AI architectureDecision FrameworkOntology
0 likes · 19 min read
Don't Overhype Ontology: A Three-Gate Framework for AI Semantic Decisions
DataFunSummit
DataFunSummit
Aug 9, 2026 · Artificial Intelligence

Ontology-Driven Knowledge Engineering for Enterprise AI Office Agents

The article analyzes the knowledge bottlenecks that hinder enterprise AI agents, proposes a three‑layer ontology‑driven architecture, details a six‑step ontology construction workflow, showcases concrete office‑automation scenarios (document review, meeting minutes, document structuring), and outlines evaluation metrics and a fast‑track rollout plan.

Agentic AIEnterprise AIOntology
0 likes · 28 min read
Ontology-Driven Knowledge Engineering for Enterprise AI Office Agents
AI Large-Model Wave and Transformation Guide
AI Large-Model Wave and Transformation Guide
May 28, 2026 · Artificial Intelligence

A/B Comparison of Direct Document Feeding vs Semantic Governance for Industrial Software Test Case Generation

The article presents a rigorous A/B experiment comparing a baseline AI that directly consumes documentation with a knowledge‑embedded approach that adds semantic governance, showing how structured data assets dramatically improve test point and test case quality in industrial software development.

A/B experimentAI testingTest Case Generation
0 likes · 27 min read
A/B Comparison of Direct Document Feeding vs Semantic Governance for Industrial Software Test Case Generation
Data Integration and Governance
Data Integration and Governance
Apr 29, 2026 · Artificial Intelligence

Is Your Data Governance Ready for the AI Race?

While AI models advance rapidly, many enterprises stumble not due to model limitations but because their data foundations are weak; the article outlines four essential data‑governance capabilities—integration, trustworthiness, unified semantics, and continuous operation—to ensure reliable, scalable AI deployments.

Continuous Operationsartificial intelligencedata quality
0 likes · 9 min read
Is Your Data Governance Ready for the AI Race?
AsiaInfo Technology: New Tech Exploration
AsiaInfo Technology: New Tech Exploration
Oct 17, 2025 · Industry Insights

How Semantic Governance Fuels AI-Ready Data Management: A Practical Roadmap

This article outlines a comprehensive, three‑stage implementation framework for semantic governance, details the essential supporting technologies, proposes new organizational roles and collaborative mechanisms, and explores future trends such as agent integration and LLM‑driven ontology evolution to empower AI‑centric enterprise data strategies.

AIenterprise transformationknowledge graph
0 likes · 26 min read
How Semantic Governance Fuels AI-Ready Data Management: A Practical Roadmap