Construct a Commonsense Knowledge Model of Activities in Urban Leisure Space with the Spreading Activation Theory

This paper presents a semantic network of commonsense knowledge that is useful in capturing human experience in ambient intelligence environments. Human behavior is composed of a series of behavior patterns. And a behavior pattern contains behavioral features, such as the objects touched by users, time, and location information, within a period of time. Consequently, in this paper, the algorithm of the spreading activation model is adopted. Each behavior node is inferred based on the possibility of what behavior may happen next and on their mutual relationships. In the spreading activation model, various weights are put into certain nodes and checked to see if some behavior nodes are enabled under such a circumstance.