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Computer Science > Computation and Language

arXiv:2211.12124 (cs)
[Submitted on 22 Nov 2022]

Title:A Large-Scale Dataset for Biomedical Keyphrase Generation

Authors:Mael Houbre, Florian Boudin, Beatrice Daille
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Abstract:Keyphrase generation is the task consisting in generating a set of words or phrases that highlight the main topics of a document. There are few datasets for keyphrase generation in the biomedical domain and they do not meet the expectations in terms of size for training generative models. In this paper, we introduce kp-biomed, the first large-scale biomedical keyphrase generation dataset with more than 5M documents collected from PubMed abstracts. We train and release several generative models and conduct a series of experiments showing that using large scale datasets improves significantly the performances for present and absent keyphrase generation. The dataset is available under CC-BY-NC v4.0 license at this https URL datasets/taln-ls2n/kpbiomed.
Comments: Accepted at the 13th International Workshop on Health Text Mining and Information Analysis (LOUHI 2022)
Subjects: Computation and Language (cs.CL)
Cite as: arXiv:2211.12124 [cs.CL]
  (or arXiv:2211.12124v1 [cs.CL] for this version)
  https://doi.org/10.48550/arXiv.2211.12124

Submission history

From: Maël Houbre [view email]
[v1] Tue, 22 Nov 2022 09:53:23 UTC (6,448 KB)
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