SAS: Spatial Activity Summarization: A Geometric & Network based approach

Given a spatial network, a spatial neighbourhood, a collection of activities, and a number of clusters to identify, the problem of geometric and network based summarization is to advise our users whether to use a network-based summarization or a geometry-based one. Network summarization is an important societal problem and has been used by athorities to curb crime [15, 5, 12] and respond to natural disasters [17, 3, 1]. Oliver et al. [17] proved, in specific cases, network based summarization is a better approach than geometry based ones whereas the existence of geometry based approaches for the last 2 decades [9] proves their acceptance with the environmental criminologists and the authorities [5]. Thus defining a classifier that gives the authorities an insight regarding the specific summarizations to follow in a specific network becomes a problem of high societal importance. Previous works have either focussed on geometry or network based approaches and none of the referenced works have been able to combine the potential of both the approaches and provide a decision metric to suggest which one to use in a particular scenario. The problem at hand can be divided into 3 sub structures, namely a decision whether to choose a geometric or a network-based summarization and based on the decision, an implementation of the two. The latter two are already proven to be computationally complex, whereas in this research we prove that the decision to choose either of the approaches is also not computationally trivial.