Pattern Recognition and Machine Intelligence (PReMI 2011) Springer, Lecture Notes in Computer Science, Vol. 6744, 2011
Authors: Maunendra Sankar Desarkar, Rahul Joshi, Sudeshna Sarkar Affiliation: Department of Computer Science & Engineering, IIT Kharagpur
Proposes a displacement-based variant of the Kendall-Tau distance metric for unsupervised evaluation of rank aggregation algorithms. The metric considers rank position differences, enabling evaluation without ground truth rankings — applicable to metasearch engines and preference aggregation systems.
Keywords: Rank Aggregation, Kendall-Tau Distance, Unsupervised Evaluation, Information Retrieval