Sweep-Line Extensions to the Multiple Object Intersection Problem: Methods and Applications in Graph Mining

Identifying and quantifying the size of multiple overlapping axis-aligned geometric objects is an essential computational geometry problem. The ability to solve this problem can effectively inform a number of spatial data mining methods and can provide support in decision making for a variety of critical applications. The state-of-the-art approach for addressing such problems resorts to an algorithmic paradigm, collectively known as the sweep-line or plane sweep algorithm. However, its application inherits a number of limitations including lack of versatility and lack of support for ad hoc intersection queries. With these limitations in mind, we design and implement a novel, exact, fast and scalable yet versatile, sweep-line based algorithm, named SLIG. The key idea of our algorithm lies in constructing an auxiliary data structure when the sweep line algorithm is applied, an intersection graph. This graph can effectively be used to provide connectivity properties among overlapping objects and to inform answers to ad hoc intersection queries. It can also be employed to find the location and size of the common area of multiple overlapping objects. SLIG performs significantly faster than classic sweep-line based algorithms, it is more versatile, and provides a suite of powerful querying capabilities. To demonstrate the versatility of our SLIG algorithm we show how it can be utilized for evaluating the importance of nodes in a trajectory network - a type of dynamic network where the nodes are moving objects (cars, pedestrians, etc.) and the edges represent interactions (contacts) between objects as defined by a proximity threshold. The key observation to address the problem is that the time intervals of these interactions can be represented as 1-dimensional axis-aligned geometric objects. Then, a variant of our SLIG algorithm, named SLOT, is utilized that effectively computes the metrics of interest, including node degree, triangle membership and connected components for each node, over time