Subsumer: a Prolog θ-subsumption engine. State-of-the-art θ-subsumption engines like Django (C) and Resumer2 (Java) are implemented in imperative languages. Since θ-subsumption is inherently a logic problem, in this paper we explore how to efficiently implement it in Prolog. θ-subsumption is an important problem in computational logic and particularly relevant to the inductive logic programming (ILP) community as it is at the core of the hypotheses coverage test which is often the bottleneck of an ILP system. Also, since most of those systems are implemented in Prolog, they can immediately take advantage of a Prolog based θ-subsumption engine. We present a relatively simple (≈1000 lines in Prolog) but efficient and general θ-subsumption engine, Subsumer. Crucial to Subsumer’s performance is the dynamic and recursive decomposition of a clause in sets of independent components. Also important are ideas borrowed from constraint programming that empower Subsumer to efficiently work on clauses with up to several thousand literals and several dozen distinct variables. Using the notoriously challenging Phase Transition dataset we show that, cputime wise, Subsumer clearly outperforms the Django subsumption engine and is competitive with the more sophisticated, state-of-the-art, Resumer2. Furthermore, Subsumer’s memory requirements are only a small fraction of those engines and it can handle arbitrary Prolog clauses whereas Django and Resumer2 can only handle Datalog clauses.
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References in zbMATH (referenced in 3 articles )
Showing results 1 to 3 of 3.
- Katzouris, Nikos; Artikis, Alexander; Paliouras, Georgios: Incremental learning of event definitions with inductive logic programming (2015)
- Santos, José; Muggleton, Stephen: When does it pay off to use sophisticated entailment engines in ILP? (2011)
- Santos, Jose; Muggleton, Stephen: Subsumer: a Prolog $\theta$-subsumption engine (2010)