Pairwise Information Retrieval Algorithm
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A Pairwise Information Retrieval Algorithm is an information retrieval algorithm that ...
References
2016
- (Lynch et al., 2016) ⇒ Corey Lynch, Kamelia Aryafar, and Josh Attenberg. (2016). “Images Don't Lie: Transferring Deep Visual Semantic Features to Large-Scale Multimodal Learning to Rank.” In: Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. ISBN:978-1-4503-4232-2 doi:10.1145/2939672.2939728
2009
- (Liu, 2009) ⇒ Tie-Yan Liu. (2009). “Learning to Rank for Information Retrieval.” In: Foundations and Trends in Information Retrieval Journal, 3(3). [http://dx.doi.org/10.1561/1500000016 doi:10.1561/1500000016
- QUOTE: Learning to rank for Information Retrieval (IR) is a task to automatically construct a ranking model using training data, such that the model can sort new objects according to their degrees of relevance, preference, or importance. Many IR problems are by nature ranking problems, and many IR technologies can be potentially enhanced by using learning-to-rank techniques. The objective of this tutorial is to give an introduction to this research direction. Specifically, the existing learning-to-rank algorithms are reviewed and categorized into three approaches: the pointwise, pairwise, and listwise approaches.