An analysis of ranking principles and retrieval strategies

Authors:
Guido Zuccon;Leif Azzopardi;C. J. Keith Van Rijsbergen
Affiliations:
School of Computing Science, University of Glasgow, Scotland, UK;School of Computing Science, University of Glasgow, Scotland, UK;School of Computing Science, University of Glasgow, Scotland, UK
Venue:
ICTIR'11 Proceedings of the Third international conference on Advances in information retrieval theory
Year:
2011

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Abstract

The assumptions underlying the Probability Ranking Principle (PRP) have led to a number of alternative approaches that cater or compensate for the PRP's limitations. All alternatives deviate from the PRP by incorporating dependencies. This results in a re-ranking that promotes or demotes documents depending upon their relationship with the documents that have been already ranked. In this paper, we compare and contrast the behaviour of state-of-the-art ranking strategies and principles. To do so, we tease out analytical relationships between the ranking approaches and we investigate the document kinematics to visualise the effects of the different approaches on document ranking.