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PatternRank - Leveraging Pretrained Language Models and Part of Speech for Unsupervised Keyphrase Extraction

Last modified Mar 23, 2023

Keyphrase extraction is the process of automatically selecting a small set of most relevant phrases from a given text. Supervised keyphrase extraction approaches need large amounts of labeled training data and perform poorly outside the domain of the training data. In this paper, we present PatternRank, which leverages pretrained language models and part-of-speech for unsupervised keyphrase extraction from single documents. Our experiments show PatternRank achieves higher precision, recall and F1-scores than previous state-of-the-art approaches. In addition, we present the KeyphraseVectorizers* package, which allows easy modification of part-of-speech patterns for candidate keyphrase selection, and hence adaptation of our approach to any domain.

*https://github.com/TimSchopf/KeyphraseVectorizers 

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Files and Subpages

Name Type Size Last Modification Last Editor
PatternRank Poster.pdf 604 KB 17.11.2022
PatternRank.pdf 322 KB 12.09.2022