Abstract: Systems and methods for identifying entities sharing a temporal pattern using bipartite graphs are described. In one embodiment, a method includes identifying a temporal pattern in a sequence of bipartite graphs for a sequence of records involving two entity types, where records of the sequence of bipartite graphs vary according to time. An embodiment may color code the edges between entity types in the sequence of bipartite graphs according to the at least one temporal pattern identified (e.g., increasing sales between a business representative and a customer). An embodiment may therefore identify a time-based relationship between at least two entities according to the coded edges. Given the identification of entities having a time-based relationships, groups of these entities may be identified and trends may be derived therefrom (e.g., increasing sales for business units of a particular geographic region).

Abstract: Systems and methods for identifying entities sharing a temporal pattern using bipartite graphs are described. In one embodiment, a method includes identifying a temporal pattern in a sequence of bipartite graphs for a sequence of records involving two entity types, where records of the sequence of bipartite graphs vary according to time. An embodiment may color code the edges between entity types in the sequence of bipartite graphs according to the at least one temporal pattern identified (e.g., increasing sales between a business representative and a customer). An embodiment may therefore identify a time-based relationship between at least two entities according to the coded edges. Given the identification of entities having a time-based relationships, groups of these entities may be identified and trends may be derived therefrom (e.g., increasing sales for business units of a particular geographic region).