Ever wondered how to detect the most influential individual, station, motorway or node in a network? It is not a normal popularity test but a mathematical way for determining a node with the most impact in the flow of information within a network. A very good way of determining nodes that are great connectors for moving from one point of a graph to another. In a real-world situation, when these nodes are removed, the movement to other nodes in the graph becomes quite challenging. With betweenness centrality, the number of paths a node is a part of is also revealed. In a connected graph, the Betweenness Centrality algorithm calculates the shortest path between nodes in the given network. The weight between nodes is quite important in determining the shortest path as factors such as frequency, capacity, time, flow and influence determine these weights.Continue reading
I have been reading research articles and thesis on the concept of relational reasoning. It is quite an interesting concept that is deeply rooted in the fields of cognitive science, neuroscience and artificial intelligence. Humans are generally regarded as relational beings as we constantly seek interaction and affection from others. The ability to discern meaningful patterns in a stream of data ensures we are not prisoners of our own senses. We utilise our senses such as sights, smell, sound and touch to encode data on a daily basis. A small portion of these data attains a sense of meaning when we find useful patterns. These patterns enable our ability to understand concepts and take necessary actions.