Keyphrase Generation: A Multi-Aspect Survey
October 11, 2019 ยท Declared Dead ยท ๐ Conference of the Open Innovations Association
"No code URL or promise found in abstract"
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Authors
Erion รano, Ondลej Bojar
arXiv ID
1910.05059
Category
cs.CL: Computation & Language
Cross-listed
cs.IR
Citations
24
Venue
Conference of the Open Innovations Association
Last Checked
4 months ago
Abstract
Extractive keyphrase generation research has been around since the nineties, but the more advanced abstractive approach based on the encoder-decoder framework and sequence-to-sequence learning has been explored only recently. In fact, more than a dozen of abstractive methods have been proposed in the last three years, producing meaningful keyphrases and achieving state-of-the-art scores. In this survey, we examine various aspects of the extractive keyphrase generation methods and focus mostly on the more recent abstractive methods that are based on neural networks. We pay particular attention to the mechanisms that have driven the perfection of the later. A huge collection of scientific article metadata and the corresponding keyphrases is created and released for the research community. We also present various keyphrase generation and text summarization research patterns and trends of the last two decades.
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