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14 February 2020 Bidirectional LSTM-CRF models for keyword extraction in Chinese sport news
Yiqi Jiang, Tongzhou Zhao, Yue Chai, Peidong Gao
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Proceedings Volume 11430, MIPPR 2019: Pattern Recognition and Computer Vision; 114300H (2020) https://doi.org/10.1117/12.2538057
Event: Eleventh International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR2019), 2019, Wuhan, China
Abstract
State-of-the-art methods of keyword extraction from news are based on traditional machine learning and their performances rely heavily on hand-crafted feature and domain-specific knowledge. In this paper, we propose a new character-based method for keyword extraction from Chinese sport news, which based bidirectional Long Short-Term Memory with Conditional Random Field (BILSTM-CRF). The experiments result shows that BILSTM-CRF can effectively improve the performance of keyword extraction in Chinese sport news.
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Yiqi Jiang, Tongzhou Zhao, Yue Chai, and Peidong Gao "Bidirectional LSTM-CRF models for keyword extraction in Chinese sport news", Proc. SPIE 11430, MIPPR 2019: Pattern Recognition and Computer Vision, 114300H (14 February 2020); https://doi.org/10.1117/12.2538057
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KEYWORDS
Machine learning
Neural networks
Computer science
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