Link Discovery has been shown to be of utter importance for the Linked Data Web. In previous works, several supervised approaches have been developed for learning link specifications out of labelled data. Most recently, genetic programming has also been utilized to learn link specifications in an unsupervised fashion by optimizing a parametrized pseudo-F-measure. The questions underlying this e...

Recent deterministic parallel programming models show promise for their ability to replay computations and reproduce bugs, but they currently require the programmer to adopt restrictive or unfamiliar parallel constructs. Deterministic OpenMP (DOMP) is a new deterministic parallel environment built on the familiar OpenMP framework. By leveraging OpenMP’s block-structured synchronization annotati...

this paper discusses the problem of allocation of constrained renewable resource to splittable activities of a single project. if the activities of stochastic projects can be split, these projects may be completed in shorter time when the available resource is constrained. it is assumed that the resource amount required to accom-plish each activity is a discrete quantity and deterministic. the ...

Non deterministic applications arise in many domains, including, stochastic optimization, multi-objectives optimization, stochastic planning, contingent stochastic planning, reinforcement learning, reinforcement learning in partially observable Markov decision processes, and conditional planning. We present a logic programming framework called non deterministic logic programs, along with a decl...

This paper considers a fuzzy programming approach for a multi-objective single machine scheduling problem when processing times of jobs are normal random variables. The probabilistic problem is converted into an equivalent deterministic programming problem. Then the fuzzy programming technique has been applied to obtain a compromise solution. A numerical example demonstrates the feasibility of ...

Most of the real-life decision-making problems have more than one conflicting and incommensurable objective functions. In this paper, we present a multiobjective two-stage stochastic linear programming problem considering some parameters of the linear constraints as interval type discrete random variables with known probability distribution. Randomness of the discrete intervals are considered f...