Intro -- Title Page -- Contents -- 1 Introduction -- 1.1 A Motivating Experiment -- 1.2 Contributions -- 1.3 Outline -- 1.4 Previously Published Work -- 2 Preliminaries -- 2.1 Notions and Notation -- 2.2 Frequent Connected Subgraph Mining -- 2.3 Embedding Computation -- 2.4 Datasets -- 3 Related Work -- 3.1 Algorithms for the SubgraphIsomorphism Problem -- 3.2 Algorithms for the FCSM Problem -- 4 Probabilistic Frequent Subtrees -- 4.1 Mining Probabilistic Frequent Subtrees -- 4.2 Experimental Evaluation -- 4.3 Summary -- 5 Boosted Probabilistic Frequent Subtrees
5.1 An Efficient Embedding Operator for Trees -- 5.2 Mining Boosted Probabilistic Frequent Subtrees -- 5.3 Exact Frequent Subtree Mining -- 5.4 Summary and Open Questions -- 6 Fast Computation -- 6.1 Complete Embeddings into Subtree Feature Spaces -- 6.2 Min-Hashing in Subtree Feature Spaces -- 6.3 Experimental Evaluation -- 6.4 Summary and Open Questions -- 7 Conclusion -- 7.1 Discussion -- 7.2 Outlook -- A HamiltonianPath for Cactus Graphs -- A.1 Three Necessary Conditions -- A.2 A Linear Time Algorithm for Cactus Graphs -- A.3 Some Statistics for Real-World Datasets -- A.4 Summary
