Enhancing Declarative Temporal Model Mining in Relational Databases: A Preliminary Study

Samuel Appleby, Giacomo Bergami, Graham Morgan · 2023

Propositionalisation tampers the running time of state-of-the-art algorithms in declarative temporal model mining, as they exhaustively generate the clauses instantiated with the results of frequent itemset mining algorithms. Existing algorithms also exploit non-indexed data representations, thus negatively affecting the overall running time. This paper proposes a novel temporal model mining algorithm, Bolt, twinning confidence and support metrics as heuristics for candidate pruning with data structures enabling fast temporal data scanning. Bolt outperforms both state-of-the-art and renditions of existing mining algorithms using KnoBAB as a library.

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