Knowledge bases (KBs) are often greatly incomplete, necessitating a demand for KB completion. The path ranking algorithm (PRA) is one of the most promising approaches to this task. Previous work on PRA usually follows a single-task learning paradigm, building a prediction model for each relation independently with its own training data. It ignores meaningful associations among certain relations...

Shortest path problem is a classical and the most widely studied phenomenon in combinatorial optimization. In a classical shortest path problem, the distance of the arcs between different nodes of a network are assumed to be certain. In some uncertain situations, the distance will be calculated as a fuzzy number depending on the number of parameters considered. This article proposes a new appro...

The critical path problem is a classical and important network optimization problem appearing in many applications, especially in planning and controlling the complex projects. However the result of classical critical path method computation cannot properly match the real-world problem. This gives rise to fuzzy environment and hence we have fuzzy critical path method. In this paper, two differe...

We consider biobjective shortest path problems in networks with fuzzy arc lengths. Considering the available studies for single objective shortest path problems in fuzzy networks, using a distance function for comparison of fuzzy numbers, we propose three approaches for solving the biobjective prob- lems. The rst and second approaches are extensions of the labeling method to solve the sing...

In this paper, we develop a new approach to deal with neutrosphic shortest path problem in a network in which each edge weight (or length) is represented as triangular fuzzy neutrosophic number. The proposed algorithm also gives the shortest path length from source node to destination node using ranking function. Finally, an illustrative example is also included to demonstrate our proposed appr...

In the present paper, Characteristics of fuzzy project network using statistical data are discussed in detail in order to calculate the fuzzy critical path, fuzzy earliest times, fuzzy latest times and fuzzy total float. Fuzzy number as fuzzy activity time is constructed using interval estimate by calculating mean, variance and standard error. A new ranking function is used to discriminate the ...

A ranking on a graph is an assignment of positive integers to its vertices such that any path between two vertices of the same rank contains a vertex of strictly larger rank. A ranking is locally minimal if reducing the rank of any single vertex produces a non ranking. A ranking is globally minimal if reducing the ranks of any set of vertices produces a non ranking. A ranking is greedy if, for ...

We derive a knowledge gradient policy for an optimal learning problem on a graph, in which we use sequential measurements to refine Bayesian estimates of individual edge values in order to learn about the best path. This problem differs from traditional ranking and selection, in that the implementation decision (the path we choose) is distinct from the measurement decision (the edge we measure)...