MDERank: A Masked Document Embedding Rank Approach for Unsupervised Keyphrase Extraction (2022.findings-acl)
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| Challenge: | Keyphrase extraction (KPE) extracts phrases in a document that provide a concise summary of the core content. |
| Approach: | They propose an unsupervised keyphrase extraction method that ranks candidates by similarity between embeddings of source document and masked document. |
| Outcome: | The proposed method outperforms state-of-the-art methods on six benchmarks . it achieves average 3.53 improvement over the existing method . |
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| Challenge: | Existing methods for keyphrase extraction are either supervised or unsupervised. |
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PromptRank: Unsupervised Keyphrase Extraction Using Prompt (2023.acl-long)
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| Challenge: | Existing keyphrase extraction methods struggle with document and candidate length discrepancies or fail to fully utilize the pre-trained language model without further fine-tuning. |
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| Challenge: | Existing methods for keyphrase extraction lack the ability to utilize keyphrase information, which may result in biased results. |
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Key2Vec: Automatic Ranked Keyphrase Extraction from Scientific Articles using Phrase Embeddings (N18-2)
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| Challenge: | Keyphrase extraction is a fundamental task in natural language processing that facilitates mapping of documents to a set of representative phrases. |
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Improving Embedding-based Unsupervised Keyphrase Extraction by Incorporating Structural Information (2023.findings-acl)
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| Challenge: | Existing unsupervised keyphrase extraction models ignore the indicative role of the highlights in certain locations, leading to wrong keyphrases extraction. |
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| Challenge: | Existing models for keyphrase generation and keyphrase extraction use a token level to generate keyphrases that do not appear in a document. |
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AGRank: Augmented Graph-based Unsupervised Keyphrase Extraction (2022.aacl-main)
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| Challenge: | Unsupervised keyphrase extraction (UKE) is highly anticipated because no labeled data is needed to train a model. |
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HyperRank: Hyperbolic Ranking Model for Unsupervised Keyphrase Extraction (2023.emnlp-main)
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| Challenge: | Existing unsupervised keyphrase extraction models overlook latent hierarchical structures when extracting keyphrases. |
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Match More, Extract Better! Hybrid Matching Model for Open Domain Web Keyphrase Extraction (2024.findings-acl)
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| Challenge: | Existing models for keyphrase extraction use noisy information to filter the salient phrases from the document. |
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Unsupervised Keyphrase Extraction by Learning Neural Keyphrase Set Function (2023.findings-acl)
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| Challenge: | Unsupervised keyphrase extraction is a task of extracting a keyphrase set that provides readers with highlevel information about the key ideas or important topics described in the document. |
| Approach: | They propose an unsupervised keyphrase extraction task that is a document-set matching problem instead of modeling the relevance between an individual phrase and the document. |
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