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Directory > Technology > Knowledge Representation

Knowledge Representation

Knowledge Representation

Welcome to Knowledge Representation! This is your go-to place for understanding how we encode and represent knowledge in AI. The ability to make sense of data sets Knowledge Representation apart. You’ll find a wide range of techniques here, from semantic networks to logic-based systems. Are you an AI researcher? A developer? Maybe a curious student? Whoever you are, you’ll find something useful here. We cover everything from foundational principles to advanced frameworks. Get ready to dive into a world that’s making AI smarter every day. This category serves as your definitive guide to the various techniques, methodologies, and frameworks employed in Knowledge Representation. Whether you’re an AI researcher working on semantic networks, a developer involved in creating intelligent systems, or a student eager to grasp the foundational principles, Knowledge Representation is your go-to category. Dive in to discover the diverse approaches, from ontology and logic-based systems to probabilistic models, that are making AI smarter and more capable.

Cycorp

Knowledge Base

FrameNet

Lexical Database

ConceptNet

Semantic Network

SUMO (Suggested Upper Merged Ontology)

Ontology

WordNet

Lexical Database

Ontotext

Knowledge Graph Platform

Protege

Ontology Editor

Knowledge Graph Conference

Conference

KMi – The Open University

Research Institute

DBpedia

Community Project
We want to make Knowledge Representation the best resource out there, and you can help. Have you stumbled upon a fresh approach to representing knowledge in AI? Or do you have category ideas like 'Semantic Networks' or 'Probabilistic Models'? We want to hear from you. Click 'Submit Suggestion' to share your thoughts. You're not just adding to a list; you're shaping a platform. A platform that aims to inform and educate a wide audience on the ins and outs of Knowledge Representation in AI. Let's build something great together.