Abstract
In this chapter, we introduce the statistical ranking framework. In order to analyze the theoretical properties of learning-to-rank methods, the very first step is to establish the right probabilistic context for the analysis. This is just what the statistical ranking framework addresses. In this chapter we will show three ranking frameworks used in the literature of learning to rank, i.e., the document ranking framework, the subset ranking framework, and the two-layer ranking framework. The discussions in this chapter set the stage for further discussions on generalization ability and statistical consistency in the following chapters.
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© 2011 Springer-Verlag Berlin Heidelberg
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Liu, TY. (2011). Statistical Ranking Framework. In: Learning to Rank for Information Retrieval. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14267-3_16
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DOI: https://doi.org/10.1007/978-3-642-14267-3_16
Publisher Name: Springer, Berlin, Heidelberg
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