Faster distance-based representative skyline and k-center along pareto front in the plane

Finding Pareto Optimal Groups: Group-based Skyline

Skyline computation, aiming at identifying a set of skyline points that are not dominated by any other point, is particularly useful for multi-criteria data analysis and decision making. Traditional skyline computation, however, is inadequate to answer queries that need to analyze not only individual points but also groups of points. To address this gap, we generalize the original skyline defin...

Skyline Queries and Pareto Optimality

Maximum Coverage Representative Skyline

Skyline queries represent a dataset by the points on its pareto frontier, but can become very large. To alleviate this problem, representative skylines select exactly k skyline points. However, existing approaches are not scaleinvariant, not stable, or must materialise the entire skyline. We introduce the maximum coverage representative skyline, which returns the k points collectively dominatin...

Efficient Skyline Queries under Weak Pareto Dominance

Skylines with partial order preference semantics often result in huge answer sets and what is worse, they cannot be computed efficiently. In this paper we will explore the evaluation of so-called restricted skyline queries with partial order preferences under the paradigm of weak Pareto dominance. Weak Pareto dominance removes all objects from skylines, which are dominated by other objects in s...

Computing the Complete Pareto Front

We give an efficient algorithm to enumerate all elements of a Pareto front in a multi-objective optimization problem in which the space of values is finite for all objectives. Our algorithm uses a feasibility check for a search space element as an oracle and minimizes the number of oracle calls that are necessary to identify the Pareto front of the problem. Given a k-dimensional search space in...