Listwise approach based on the cross‐correntropy for learning to rank
Mintao Wu, Jihua Zhu, Jun Wang, Shanmin Pang, Yaochen Li · Electronics Letters · 2018
The problem of learning to rank is addressed and a novel listwise approach by taking document retrieval as an example is proposed. It first introduces the concept of cross‐correntropy into learning to rank and then proposes the listwise loss function based on the cross‐correntropy between the ranking list given by the label and the one predicted by training model. The use of the cross‐correntropy loss leads to the development of the listwise approach called ListCCE, which employs the gradient descent algorithm to train a neural network model. Experimental results tested on publicly available data sets show that the proposed approach performs better than some existing approaches.