LongKey: Keyphrase Extraction for Long Documents

In an era of information overload, manually annotating the vast and growing corpus of documents and scholarly papers is increasingly impractical. Automated keyphrase extraction addresses this challenge by identifying representative terms within texts. However, most existing methods focus on short documents (up to 512 tokens), leaving a gap in processing long-context documents. In this paper, we introduce LongKey, a novel framework for extracting keyphrases from lengthy documents, which uses an encoder-based language model to capture extended text intricacies. LongKey uses a max-pooling embedder to enhance keyphrase candidate representation. Validated on the comprehensive LDKP datasets and six diverse, unseen datasets, LongKey consistently outperforms existing unsupervised and language model-based keyphrase extraction methods. Our findings demonstrate LongKey’s versatility and superior performance, marking an advancement in keyphrase extraction for varied text lengths and domains.

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Publication Details

Published
2024-12-15
DOI
https://doi.org/10.1109/bigdata62323.2024.10824946
Citations
3
Primary Topic
Advanced Text Analysis Techniques
Type
article
Field-Weighted Citation Impact
1.04

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article

LongKey: Keyphrase Extraction for Long Documents

Cinthia Obladen de Almendra Freitas‍, Radu State, Jean Paul Barddal, Jeovane Honorio Alves
3 citations
Advanced Text Analysis Techniques
1.04
article

LongKey: Keyphrase Extraction for Long Documents

Cinthia Obladen de Almendra Freitas‍, Radu State, Jean Paul Barddal, Jeovane Honorio Alves
article en
3 citations

Abstract

In an era of information overload, manually annotating the vast and growing corpus of documents and scholarly papers is increasingly impractical. Automated keyphrase extraction addresses this challenge by identifying representative terms within texts. However, most existing methods focus on short documents (up to 512 tokens), leaving a gap in processing long-context documents. In this paper, we introduce LongKey, a novel framework for extracting keyphrases from lengthy documents, which uses an encoder-based language model to capture extended text intricacies. LongKey uses a max-pooling embedder to enhance keyphrase candidate representation. Validated on the comprehensive LDKP datasets and six diverse, unseen datasets, LongKey consistently outperforms existing unsupervised and language model-based keyphrase extraction methods. Our findings demonstrate LongKey’s versatility and superior performance, marking an advancement in keyphrase extraction for varied text lengths and domains.

University of Luxembourg (LU)
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
Openalex Percentile: Top 18%
Advanced Text Analysis Techniques
1.04
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