Pointwise Learning-to-Rank Algorithm
(Redirected from Pointwise Ordinal Regression Algorithm)
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A Pointwise Learning-to-Rank Algorithm is an supervised ranking algorithm that directly predicts the ordinal value for an item.
- Context:
- It can be implemented by a pointwise LTR system (to solve a pointwise LTR task).
- …
- Example(s):
- Counter-Example(s):
- See: Classification (Machine Learning), Supervised Learning, Ordinal Regression.
References
2017
- (Wikipedia, 2017) ⇒ https://en.wikipedia.org/wiki/learning_to_rank#Pointwise_approach Retrieved:2017-9-13.
- In this case it is assumed that each query-document pair in the training data has a numerical or ordinal score. Then learning-to-rank problem can be approximated by a regression problem — given a single query-document pair, predict its score.
A number of existing supervised machine learning algorithms can be readily used for this purpose. Ordinal regression and classification algorithms can also be used in pointwise approach when they are used to predict score of a single query-document pair, and it takes a small, finite number of values.
- In this case it is assumed that each query-document pair in the training data has a numerical or ordinal score. Then learning-to-rank problem can be approximated by a regression problem — given a single query-document pair, predict its score.
2017b
- (Wikipedia, 2017) ⇒ https://en.wikipedia.org/wiki/Learning_to_rank#List_of_methods Retrieved:2017-9-13.
- A partial list of published learning-to-rank algorithms is shown below with years of first publication of each method
(Note: as most supervised learning algorithms can be applied to pointwise case, only those methods which are specifically designed with ranking in mind are shown):
- A partial list of published learning-to-rank algorithms is shown below with years of first publication of each method
Year Name Type Notes 1989 OPRF pointwise Polynomial regression (instead of machine learning, this work refers to pattern recognition, but the idea is the same) 1992 SLR pointwise Staged logistic regression 2002 Pranking pointwise Ordinal regression. 2007 McRank pointwise 2010 CRR pointwise & pairwise Combined Regression and Ranking. Uses stochastic gradient descent to optimize a linear combination of a pointwise quadratic loss and a pairwise hinge loss from Ranking SVM.