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Neural document expansion for ad-hoc information retrieval
December 27, 2020 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
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Authors
Cheng Tang, Andrew Arnold
arXiv ID
2012.14005
Category
cs.IR: Information Retrieval
Cross-listed
cs.AI,
cs.CL,
cs.LG
Citations
3
Venue
arXiv.org
Last Checked
4 months ago
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.
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