Abstract
Most of the recent proposals in tabling technology were designed as a means to improve some practical deficiencies of current tabling execution models that reduce their applicability in particular applications. The discussion we address in this paper was also motivated by practical deficiencies we encountered, in particular, on the table storage mechanisms used for tabling support. To improve such mechanisms, we propose two new implementation techniques that make tabling models more efficient when dealing with incomplete tables and more robust when recovering memory from the table space. To validate our proposals, we have implemented them in the YapTab tabling system as an elegant extension of the original design.

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Inductive Logic Programming (ILP) is a powerful and well-developed abstraction for multi-relational data mining techniques. Despite the considerable success of ILP, deployed ILP systems still have efficiency problems when applied to complex problems. In this paper we propose a novel technique that avoids the procedure of deducing each example to evaluate each constructed clause. The technique is based on the Mode Directed Inverse Entailment approach to ILP, where a bottom clause is generated for each example and the generated clauses are subsets of the literals of such bottom clause. We propose to store in a prefix-tree all clauses that can be generated from all bottom clauses together with some extra information. We show that this information is sufficient to estimate the number of examples that can be deduced from a clause and present an ILP algorithm that exploits this representation. We also present an extension of the algorithm where each prefix-tree is computed only once (compiled) per example. The evaluation of hypotheses requires only basic and efficient operations on trees. This proposal avoids re-computation of hypothesis' value in theory-level search, in cross-validation evaluation procedures and in parameter tuning. Both proposals are empirically evaluated on real applications and considerable speedups were observed.

Abstract
This paper presents the logic programming concept of thread-based competitive or-parallelism, which combines the original idea of competitive or-parallelism with committed-choice nondeterminism and speculative threading. In thread-based competitive or-parallelism, an explicit; disjunction of subgoals is interpreted as a set of concurrent alternatives, each running in its own thread. The individual subgoals usually correspond to predicates implementing different procedures that, depending on the problem specifics, are expected to either fail or succeed with different performance levels. The subgoals compete for providing an answer and the first successful subgoal leads to the termination of the remaining ones. We discuss the implementation of thread-based competitive or-parallelism in the context of Logtalk, an object-oriented logic programming language, and present experimental results.