Neural document expansion for ad-hoc information retrieval
Information Retrieval
2020-12-29 v1 Artificial Intelligence
Computation and Language
Machine Learning
Abstract
Recently, Nogueira et al. [2019] proposed a new approach to document expansion based on a neural Seq2Seq model, showing significant improvement on short text retrieval task. However, this approach needs a large amount of in-domain training data. In this paper, we show that this neural document expansion approach can be effectively adapted to standard IR tasks, where labels are scarce and many long documents are present.
Cite
@article{arxiv.2012.14005,
title = {Neural document expansion for ad-hoc information retrieval},
author = {Cheng Tang and Andrew Arnold},
journal= {arXiv preprint arXiv:2012.14005},
year = {2020}
}