Knowledge Graph

Implicit in the name “knowledge graph” is, of course, that a knowledge graph represent knowledge, and do so using a graph structure.

Knowledge graph meaning is expressed as structure.

Knowledge graph statements are unambiguous.

Knowledge graphs use a limited set of relation types.

In order for knowledge graphs statements to be unambiguous, they need to be composed of unambiguous units. All identified entities in a knowledge graph, including types and relations, must be identified using global identifiers with unambiguous denotation.


We will demonstrate a reusable framework for developing knowledge graphs that supports general, open-ended development of knowledge curation, interaction, and inference. Knowledge graphs need to be easily maintainable and usable in sometimes complex application settings.

We demonstrate the usage of our FoodKG [3], a food knowledge graph designed to assist in food recommendation.

The proliferation of recipes and other food information on the Web presents an opportunity for discovering and organizing diet-related knowledge into a knowledge graph.

With the hype around blockchain technologies, misinformation on ‘get rich quick’ scams are becoming rampant. In this work, we describe a solution that puts in the groundwork to identify fraudulent users and track them across multiple blockchains using semantic modeling.

The proliferation of recipes and other food information on the Web presents an opportunity for discovering and organizing diet-related knowledge into a knowledge graph.

Knowledge graphs can be used to help scientists integrate and explore their data in novel ways. NanoMine, built with the Whyis knowledge graph framework, integrates diverse data from over 1,700 polymer nanocomposite experiments.

Commonsense knowledge is essential for many AI applications, including those in natural language processing, visual processing, and planning. Consequently, many sources that include commonsense knowledge have been designed and constructed over the past decades.

Prepares students for research in knowledge graphs.