期刊
DIGITAL LIBRARIES AND MULTIMEDIA ARCHIVES, IRCDL 2018
卷 806, 期 -, 页码 180-187出版社
SPRINGER-VERLAG BERLIN
DOI: 10.1007/978-3-319-73165-0_18
关键词
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To achieve state-of-the-art performance, keyphrase extraction systems rely on domain-specific knowledge and sophisticated features. In this paper, we propose a neural network architecture based on a Bidirectional Long Short-Term Memory Recurrent Neural Network that is able to detect the main topics on the input documents without the need of defining new hand-crafted features. A preliminary experimental evaluation on the well-known INSPEC dataset confirms the effectiveness of the proposed solution.
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