Work

Multi-Document Keyphrase Extraction: Dataset, Baselines and Review

Year: 2021

Type: preprint

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.

Source: arXiv (Cornell University)

DOI: 10.48550/arxiv.2110.01073

Authors: Shapira, Ori, Pasunuru, Ramakanth, Dagan, Ido, Amsterdamer, Yael

Institutions: Bar-Ilan University, University of North Carolina at Chapel Hill

Language: English

Topic: Advanced Text Analysis Techniques

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

Funder: Deutsche Forschungsgemeinschaft

Award: G7805275943

OpenAlex ID: W4286911901

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Cited by: 1

Related to: 10