Popular ranking

Zuylen, Anke van; Schalekamp, Frans; Williamson, David P.

doi:10.1016/j.dam.2012.07.006

Cited by 12 publications

(24 citation statements)

References 6 publications

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“…In [15], a new approach to the problem of aggregating preferences of multiple agents based on the notion of popular ranking is introduced: a ranking of a set of elements is popular if there is no other permutation of the elements that a majority of the voters prefer. They analyzed the computational complexity and proved it is NP-hard to find a ranking with a majority of preferences.…”

Section: Related Workmentioning

confidence: 99%

“…In the aggregation ranking problem a way of measuring how different two rankings are is required, and distances are the conventional tool to do that. A common approach to this problem is to find a permutation that minimizes the sum of the distances to the voters rankings, where in principle any distance (-like), function on permutations can be used [15]. The most frequently used distance measures among rankings are the Spearman footrule distance and the Kendall τ distance [16]; the Spearman footrule distance between two given rankings is defined as the sum, over all the candidates i of the absolute differences between the ranks of i with respect to the two rankings; the Kendall distance between two rankings is given by the minimum number of pairwise adjacent transpositions needed to transform one ranking into another.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A New Method For Personnel Selection Based On Ranking Aggregation Using A Reinforcement Learning Approach

Filiberto¹,

Pérez²,

Nowé³

2018

CyS

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In this paper propose a new approach to the problem of aggregating rankings for obtaining an overall ranking. This is also referred to as the aggregation ranking in the personnel selection problem. Our approach is based on a distance measure between the individual and the overall ranking, and looks for the solution that minimizes the disagreement between the input rankings and the resulting aggregation. The method uses a reinforcement learning approach to build the aggregation and its performance and comparison with other approaches shows promising results.

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Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A New Method For Personnel Selection Based On Ranking Aggregation Using A Reinforcement Learning Approach

Filiberto¹,

Pérez²,

Nowé³

2018

CyS

View full text Add to dashboard Cite

show abstract

“…Actually, the greater is the similarity between the given rankings by the employers, the higher the conflict of interest. As a ranking is a permutation of N values, the similarity between rankings can be expressed using distances between permutations [26,14]. One of the most frequently used distance measures between rankings is the Spearman footrule distance [27].…”

Section: Formalization Of the Problem Of Personnel Selection In A Commentioning

confidence: 99%

“…Rank aggregation is the problem of combining multiple rankings in a single ranking; that is, given a set of N permutations of n elements, to identify the permutation which represents this set in the best way. A common approach to this problem is to find a permutation that minimizes the sum of the distances to each ranking, where in principle any distance(-like) function on permutations can be used [12,13,14].…”

Section: Introductionmentioning

confidence: 99%

Personnel Selection in a Competitive Environment

Bello

García-Lorenzo

et al. 2016

CyS

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The personnel selection problem is a classical decision making problem. It refers to the process of choosing candidates who match, possibly to some degree, the qualifications required to perform a certain job. Personnel selection is an important activity for organizations and usually the outcome of a personnel selection method is an overall ranking of the candidates. This paper introduces two new results. First, we propose an alternative approach to the personnel selection problem in which the interaction of two competing decision makers (employers), who must select two subsets of persons from a common list of candidates, is considered. Second, given the rankings of the candidates for each employer, a method based on the game theory is presented to solve this problem.

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“…In another recent work, Zuylen et al. ( 2014 ) consider the problem of finding a popular ranking from a computational viewpoint. In their framework, given a set of alternatives, each member of a set of agents proposes her ideal solution, i.e., individual ranking of the alternatives.…”

Section: Introductionmentioning

confidence: 99%

It is difficult to tell if there is a Condorcet spanning tree

Darmann

2016

Math Meth Oper Res

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We apply the well-known Condorcet criterion from voting theory outside of its classical framework and link it with spanning trees of an undirected graph. In situations in which a network, represented by a spanning tree of an undirected graph, needs to be installed, decision-makers typically do not agree on the network to be implemented. Instead, each of these decision-makers has her own ideal conception of the network. In order to derive a group decision, i.e., a single spanning tree for the entire group of decision-makers, the goal would be a spanning tree that beats each other spanning tree in a simple majority comparison. When comparing two dedicated spanning trees, a decision-maker will be considered to be more satisfied with the one that is “closer” to her proposal. In this context, the most basic and natural measure of distance is the usual set difference: we simply count the number of edges the spanning tree has in common with the proposal of the decision-maker. In this work, we show that it is computationally intractable to decide (1) if such a spanning tree exists, and (2) if a given spanning tree satisfies the Condorcet criterion.

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Popular ranking

Cited by 12 publications

References 6 publications

A New Method For Personnel Selection Based On Ranking Aggregation Using A Reinforcement Learning Approach

A New Method For Personnel Selection Based On Ranking Aggregation Using A Reinforcement Learning Approach

Personnel Selection in a Competitive Environment

It is difficult to tell if there is a Condorcet spanning tree

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