1. A method for semi-supervised insight discovery, the method being implemented by one or more data processors and comprising: seeking, by at least one data processor, pair-wise relationships between large numbers of entities, in a variety of domain specific contexts, from appropriately filtered and customized transaction data; representing, by at least one data processor, the pair-wise relationships between the entities in a graph structure containing a set of nodes representing entities, and a set of edges representing strength of relationships between pairs of nodes; discovering, by at least one data processor, insights in the form of relationship patterns of interest that may be projected or scored on individual or groups of transactions or customers; and using, by at least one data processor, said insights to make data-driven-decisions for a variety of business goals; said graph structure comprising any of the following types of structures: a sub-graph comprising a subset of a graph, created by picking a subset of nodes and edges from an original graph, a sub-graph comprising any of: node based sub-graphs which are created by selecting a subset of the nodes and by keeping only those edges between selected nodes; and edge based sub-graphs which are created by pruning a set of edges from the graph and removing all nodes that are rendered disconnected from the graph; a neighborhood of a target product comprising a sub-graph that contains the target product and all the products that are connected to the target product with consistency strength above a predefined threshold to show the top most affiliated products for a given target product; a bundle structure comprising a sub-set of products wherein each product in the bundle has a high consistency connection with all the other products in the bundle, wherein each product in a bundle is assigned a product density with respect to the bundle which is high if the product has high consistency connection with other products in the bundle and low otherwise; and a bridge structure comprising a collection of two or more, otherwise disconnected, product groups that are bridged by one or more bridge product(s).
1. A method for semi-supervised insight discovery, the method being implemented by one or more data processors and comprising: seeking, by at least one data processor, pair-wise relationships between large numbers of entities, in a variety of domain specific contexts, from appropriately filtered and customized transaction data; representing, by at least one data processor, the pair-wise relationships between the entities in a graph structure containing a set of nodes representing entities, and a set of edges representing strength of relationships between pairs of nodes; discovering, by at least one data processor, insights in the form of relationship patterns of interest that may be projected or scored on individual or groups of transactions or customers; and using, by at least one data processor, said insights to make data-driven-decisions for a variety of business goals; said graph structure comprising any of the following types of structures: a sub-graph comprising a subset of a graph, created by picking a subset of nodes and edges from an original graph, a sub-graph comprising any of: node based sub-graphs which are created by selecting a subset of the nodes and by keeping only those edges between selected nodes; and edge based sub-graphs which are created by pruning a set of edges from the graph and removing all nodes that are rendered disconnected from the graph; a neighborhood of a target product comprising a sub-graph that contains the target product and all the products that are connected to the target product with consistency strength above a predefined threshold to show the top most affiliated products for a given target product; a bundle structure comprising a sub-set of products wherein each product in the bundle has a high consistency connection with all the other products in the bundle, wherein each product in a bundle is assigned a product density with respect to the bundle which is high if the product has high consistency connection with other products in the bundle and low otherwise; and a bridge structure comprising a collection of two or more, otherwise disconnected, product groups that are bridged by one or more bridge product(s). 2. The method of claim 1 , said transactions comprising transactions in a retail domain among customers buying products at retailers in successive visits, each visit resulting in a transaction of a set of one or more products; wherein retail transaction data comprise a time stamped sequence of market baskets.