Learning to Rank Short Text Pairs with Convolutional Deep Neural Networks

Abstract

Learning a similarity function between pairs of objects is at the core of learning to rank approaches. In information retrieval tasks we typically deal with query-document pairs, in question answering -- question-answer pairs. However, before learning can take place, such pairs needs to be mapped from the original space of symbolic words into some feature… (More)
DOI: 10.1145/2766462.2767738

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@inproceedings{Severyn2015LearningTR, title={Learning to Rank Short Text Pairs with Convolutional Deep Neural Networks}, author={Aliaksei Severyn and Alessandro Moschitti}, booktitle={SIGIR}, year={2015} }