Consensus of rankings.

Rankings are widely used in many information systems. In information retrieval, a ranking is a list of ordered documents, in which a document with lower position has higher ranking score than the documents behind it. This paper studies the consensus measure for a given set of rankings, in order to understand the degree to which the rankings agree and the extent to which the rankings are related. The proposed multi-facet approach, without the need for pairwise comparison between rankings, allows to measure the consensus in a set of rankings, with respect to the length of common patterns, the number of common patterns for a given length, and the number of all common patterns. The experiments show that the proposed approach can be used to compare the search engines in terms of closeness of the returned results when semantically related key words are sent to them.