Semantic Association Identification and Knowledge Discovery for National Security Applications "Our goal is to research new techniques and improving effectiveness of techniques to identify semantic associations and knowledge discovery by exploiting a large knowledge base. Specific objectives include (a) ontology driven lazy semantic metadata extraction (i.e., annotation) to complement traditional active metadata extraction techniques, and (c) formal modeling and high-performance computation of semantic association discovery including ontology-based contextual processing and relevancy ranking of interesting relationships."
From the project report: "The nai?ve algorithm to find all paths between 2 nodes in a directed graph  shown below is a recursive implementation of a depth-first search. Our first implementation of the ?-path operator is based on this algorithm."
"Our initial implementation of the ?-Intersect operator is based on the ?-path operator. It searches for nodes where two ?-paths intersect (see Figure 5). We recognize the fact that there could be multiple intersection points for the ?-paths. Hence our implementation returns the sequence of nodes that are common between 2 ?-paths."
"The goal of ?-Iso is to take two resources as input and discover all paths that are “isomorphic” in both resources..."
Also, Semantic Association Identification and Knowledge Discovery for National Security Applications and Context-Aware Semantic Association Ranking.