Multi-Document Keyphrase Extraction: Dataset, Baselines and Review

Ori Shapira, Ramakanth Pasunuru, Ido Dagan, Yael Amsterdamer

Research output: Working paper / PreprintPreprint

Abstract

Keyphrase extraction has been extensively researched within the single-document setting, with an abundance of methods, datasets and applications. In contrast, multi-document keyphrase extraction has been infrequently studied, despite its utility for describing sets of documents, and its use in summarization. Moreover, no prior dataset exists for multi-document keyphrase extraction, hindering the progress of the task. Recent advances in multi-text processing make the task an even more appealing challenge to pursue. To stimulate this pursuit, we present here the first dataset for the task, MK-DUC-01, which can serve as a new benchmark, and test multiple keyphrase extraction baselines on our data. In addition, we provide a brief, yet comprehensive, literature review of the task.
Original languageEnglish
PublisherarXiv preprint arXiv:1508.02374
Number of pages12
DOIs
StatePublished - 3 Oct 2021

Keywords

  • Computation and Language (cs.CL)
  • FOS: Computer and information sciences

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