$O(p \log d)$ Subgraph Isomorphism using Stigmergic Swarming Agents
By: H. Van Dyke Parunak
Potential Business Impact:
Finds hidden patterns in complex data faster.
Subgraph isomorphism compares two graphs (sets of nodes joined by edges) to determine whether they contain a common subgraph. Many applications require identifying the subgraph, not just deciding its existence. A particularly common use case, using graphs with labeled nodes, seeks to find instances of a smaller pattern graph with $p$ nodes in the larger data graph with $d$ nodes. The problem is NP-complete, so that na\"ive solutions are exponential in $p + d$. A wide range of heuristics have been proposed, with the best complexity $O(p^2d^2)$. This paper outlines ASSIST (Approximate Swarming Subgraph Isomorphism through Stigmergy), inspired by the ant colony optimization approach to the traveling salesperson problem. ASSIST is linearithmic, $O(p \log d)$, and also supports matching problems (such as temporally ordered edges, inexact matches, and missing nodes or edges in the data graph) that frustrate other heuristics.
Similar Papers
Stigmergic Swarming Agents for Fast Subgraph Isomorphism
Multiagent Systems
Finds hidden patterns in connected data faster.
Finding Order-Preserving Subgraphs
Data Structures and Algorithms
Finds matching patterns in ordered data.
Semi-Random Graphs, Robust Asymmetry, and Reconstruction
Discrete Mathematics
Makes computer networks more predictable and secure.