Knowledge Representation and Reasoning with Graph Databases

Knowledge Representation and Reasoning with Graph Databases

Just in case you aren’t following Marko A. Rodriguez:

A graph database and its ecosystem of technologies can yield elegant, efficient solutions to problems in knowledge representation and reasoning. To get a taste of this argument, we must first understand what a graph is. A graph is a data structure. There are numerous types of graph data structures, but for the purpose of this post, we will focus on a type that has come to be known as a property graph. A property graph denotes vertices (nodes, dots) and edges (arcs, lines). Edges in a property graph are directed and labeled/typed (e.g. “marko knows peter”). Both vertices and edges (known generally as elements) can have any number of key/value pairs associated with them. These key/value pairs are called properties. From this foundational structure, a suite of questions can be answered and problems solved.

See the post for the details.

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