Efficient Frequent Connected Induced Subgraph Mining in Graphs of Bounded Tree-Width

Abstract

AbstractWe study the frequent connected induced subgraph mining problem, i.e., the problem of listing all connected graphs that are induced subgraph isomorphic to a given number of transaction graphs. We first show that this problem cannot be solved for arbitrary transaction graphs in output polynomial time (if P ≠ NP) and then prove that for graphs of bounded tree-width, frequent connected induced subgraph mining is possible in incremental polynomial time by levelwise search. Our algorithm is an adaptation of the technique developed for frequent connected subgraph mining in bounded tree-width graphs. While the adaptation is relatively natural for many steps of the original algorithm, we need entirely different combinatorial arguments to show the correctness and efficiency of the new algorithm. Since induced subgraph isomorphism between bounded tree-width graphs is NP-complete, the positive result of this paper provides another example of efficient pattern mining with respect to computationally intractable pattern matching operators.KeywordsPolynomial TimeConnected GraphFrequent PatternPattern MiningSubgraph IsomorphismThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.