TY - GEN
T1 - Weighted rank aggregation via relaxed integer programming
AU - Raisali, Fardad
AU - Hassanzadeh, Farzad Farnoud
AU - Milenkovic, Olgica
PY - 2013
Y1 - 2013
N2 - We propose a new family of algorithms for bounding/approximating the optimal solution of rank aggregation problems based on weighted Kendall distances. The algorithms represent linear programming relaxations of integer programs that involve variables reflecting partial orders of three or more candidates. Our simulation results indicate that the linear programs give near-optimal performance for a number of important voting parameters, and outperform methods based on PageRank and Weighted Bipartite Matching.
AB - We propose a new family of algorithms for bounding/approximating the optimal solution of rank aggregation problems based on weighted Kendall distances. The algorithms represent linear programming relaxations of integer programs that involve variables reflecting partial orders of three or more candidates. Our simulation results indicate that the linear programs give near-optimal performance for a number of important voting parameters, and outperform methods based on PageRank and Weighted Bipartite Matching.
UR - http://www.scopus.com/inward/record.url?scp=84890367533&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84890367533&partnerID=8YFLogxK
U2 - 10.1109/ISIT.2013.6620729
DO - 10.1109/ISIT.2013.6620729
M3 - Conference contribution
AN - SCOPUS:84890367533
SN - 9781479904464
T3 - IEEE International Symposium on Information Theory - Proceedings
SP - 2765
EP - 2769
BT - 2013 IEEE International Symposium on Information Theory, ISIT 2013
T2 - 2013 IEEE International Symposium on Information Theory, ISIT 2013
Y2 - 7 July 2013 through 12 July 2013
ER -