LongKey: Keyphrase Extraction for Long Documents
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Abstract (arXiv)
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.
Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 15 of its 29 references that are in the map. First posted on arXiv 26 Nov 2024.
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15 of 29 references.
References · 15
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3 more
- 2022Hyperbolic Relevance Matching for Neural Keyphrase Extractioncited by 7
- 2023Enhancing Keyphrase Extraction from Long Scientific Documents using Graph Embeddingscited by 3
- 2023Detecting Relevant Information in High-Volume Chat Logs: Keyphrase Extraction for Grooming and Drug Dealing Forensic Analysiscited by 2
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Citing papers per year: 2026: 1.
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