Supervised Rank Prediction Task

A Supervised Rank Prediction Task is a data-driven rank prediction task that is a supervised ordinal prediction task.

• AKA: Learing-to-Rank (LTR).
• Context:
  • It can be solved by a Supervised Rank Prediction System (that implements a supervised rank prediction algorithm).
• Example(s):
  • predict the rank of ads that will optimize clickthrough rate.
  • …
• Counter-Example(s):
  • an Ordinal Regression Task.
  • an Unsupervised Rank Prediction Task.
  • a Supervised Class Prediction Task.
  • a Supervised Numeric-Value Prediction Task.
• See: Supervised IR.

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References

2009

• (Liu, 2009) ⇒ Tie-Yan Liu. (2009). “Learning to Rank for Information Retrieval.” Foundations and Trends ® in Information Retrieval, 3(3).

1999

• (Herbrich et al., 1999) ⇒ Ralf Herbrich, Thore Graepel, and Klaus Obermayer. (1999). “Support Vector Learning for Ordinal Regression.” In: Proceedings of the Ninth International Conference on Artificial Neural Networks.
  • QUOTE: Problems of ordinal regression arise in many fields, e.g., in information retrieval (Herbrich et al. 1998), in econometric models (Tangian and Gruber 1995), and in classical statistics (McCullagh 1980; Anderson 1984). They can be related to the standard machine learning paradigm as follows: ...

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