Oct 13, 2021 · We propose a novel unsupervised embedding-based KPE approach, Masked Document Embedding Rank (MDERank), to address this problem by leveraging a mask strategy.

May 22, 2022 · Keyphrase extraction (KPE) automatically ex- tracts phrases in a document that provide a concise summary of the core content, which benefits ...

One is teaching the encoder to distinguish documents masked with keyphrases and non-keyphrases. The other is further pre-training the encoder with a MLM task.

A novel unsupervised embedding-based KPE approach, Masked Document Embedding Rank (MDERank), is proposed to address the problem of performance degradation ...

This is code for paper: MDERank: A Masked Document Embedding Rank Approach for Unsupervised Keyphrase Extraction. Data is from OpenNMT-kpg-release and SIFRank.

PDF | On Jan 1, 2022, Linhan Zhang and others published MDERank: A Masked Document Embedding Rank Approach for Unsupervised Keyphrase Extraction | Find, ...

Aug 1, 2024 · Bibliographic details on MDERank: A Masked Document Embedding Rank Approach for Unsupervised Keyphrase Extraction.

MDERank: A Masked Document Embedding Rank Approach for Unsupervised Keyphrase Extraction ... Hyperbolic Relevance Matching for Neural Keyphrase Extraction.

Oct 13, 2021 · In this paper, we propose a novel unsupervised keyword extraction method by leveraging the BERT-based model to select and rank candidate keyphrases with a MASK ...

Feb 28, 2023 · In this paper, we propose a novel unsuper- vised embedding-based KPE method, denoted by. Masked Document Embedding Rank (MDERank), to address ...