Group decision support with the analytic hierarchy process
Decision Support Systems
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Efficient similarity search and classification via rank aggregation
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
Optimal Allocation of Proposals to Reviewers to Facilitate Effective Ranking
Management Science
An agent model based on ideas of concordance and discordance for group ranking problems
Decision Support Systems
Methodologies and Algorithms for Group-Rankings Decision
Management Science
Journal of Artificial Intelligence Research
An approach to group ranking decisions in a dynamic environment
Decision Support Systems
Hi-index | 0.00 |
The group ranking problem consists of constructing coherent aggregated results from preference data provided by decision makers. Traditionally, the output of a group ranking problem can be classified into ranking lists and maximum consensus sequences. In this study, we propose a consensus preference graph approach to represent the coherent aggregated results of users' preferences. The advantages of our approach are that (1) the graph is built based on users' consensuses, (2) the graph can be understood intuitively, and (3) the relationships between items can be easily seen. An algorithm is developed to construct the consensus preference graph from users' total ranking data. Finally, extensive experiments are carried out using synthetic and real data sets. The experimental results indicate that the proposed method is computationally efficient, and can effectively identify consensus graphs.