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Jingren Zhang, Fang?ai Liu, Weizhi Xu and Hui Yu
Convolutional neural networks (CNN) and long short-term memory (LSTM) have gained wide recognition in the field of natural language processing. However, due to the pre- and post-dependence of natural language structure, relying solely on CNN to implement...
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Lin He, Shengnan Wang and Xinran Cao
Shipping Enterprise Credit Named Entity Recognition (NER) aims to recognize shipping enterprise credit entities from unstructured shipping enterprise credit texts. Aiming at the problem of low entity recognition rate caused by complex and diverse entitie...
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Yujie Zhang, Lei Zhang, Duo Sun, Kai Jin and Yu Gu
Wind power generation is a renewable energy source, and its power output is influenced by multiple factors such as wind speed, direction, meteorological conditions, and the characteristics of wind turbines. Therefore, accurately predicting wind power is ...
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Yao Qin, Yiping Shi, Xinze Hao and Jin Liu
Microblog is an important platform for mining public opinion, and it is of great value to conduct emotional analysis of microblog texts during the current epidemic. Aiming at the problem that most current emotional classification methods cannot effective...
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Weijun Pan, Peiyuan Jiang, Zhuang Wang, Yukun Li and Zhenlong Liao
In recent years, the emergence of large-scale pre-trained language models has made transfer learning possible in natural language processing, which overturns the traditional model architecture based on recurrent neural networks (RNN). In this study, we c...
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Kexin Bao, Jinqiang Bi, Miao Gao, Yue Sun, Xuefeng Zhang and Wenjia Zhang
According to the statistics of water transportation accidents, collision accidents are on the rise as the shipping industry has expanded by leaps and bounds, and the water transportation environment has become more complex, which can result in grave cons...
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Ziwen Gao, Zhiyi Li, Jiaying Luo and Xiaolin Li
This paper describes the construction a short-text aspect-based sentiment analysis method based on Convolutional Neural Network (CNN) and Bidirectional Gating Recurrent Unit (BiGRU). The hybrid model can fully extract text features, solve the problem of ...
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Runyu Fan, Lizhe Wang, Jining Yan, Weijing Song, Yingqian Zhu and Xiaodao Chen
Constructing a knowledge graph of geological hazards literature can facilitate the reuse of geological hazards literature and provide a reference for geological hazard governance. Named entity recognition (NER), as a core technology for constructing a ge...
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Shiqian Guo, Yansun Huang, Baohua Huang, Linda Yang and Cong Zhou
This paper proposed a method for improving the XLNet model to address the shortcomings of segmentation algorithm for processing Chinese language, such as long sub-word lengths, long word lists and incomplete word list coverage. To address these issues, w...
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Wenjing Yuan, Lin Yang, Qing Yang, Yehua Sheng and Ziyang Wang
Archaeological site text is the main carrier of archaeological data at present, which contains rich information. How to efficiently extract useful knowledge from the massive unstructured archaeological site texts is of great significance for the mining a...
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Yibo Liu, Qingyun Zuo, Xu Wang and Teng Zong
Entity relation extraction mainly extracts relations from text, which is one of the important tasks of natural language processing. At present, some special fields have insufficient data; for example, agriculture, the metallurgical industry, etc. There i...
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Li Qing, Weng Linhong and Ding Xuehai
Medical text categorization is a specific area of text categorization. Classification for medical texts is considered a special case of text classification. Medical text includes medical records and medical literature, both of which are important clinica...
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Jawaher Alghamdi, Yuqing Lin and Suhuai Luo
The prevalence of fake news on social media has led to major sociopolitical issues. Thus, the need for automated fake news detection is more important than ever. In this work, we investigated the interplay between news content and users? posting behavior...
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Duo Sun, Lei Zhang, Kai Jin, Jiasheng Ling and Xiaoyuan Zheng
Aiming at the imbalance of industrial control system data and the poor detection effect of industrial control intrusion detection systems on network attack traffic problems, we propose an ETM-TBD model based on hybrid machine learning and neural network ...
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Grigorios-Aris Cheimariotis and Nikolaos Mitianoudis
This work describes a methodology for sound event detection in domestic environments. Efficient solutions in this task can support the autonomous living of the elderly. The methodology deals with the ?Challenge on Detection and Classification of Acoustic...
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Jawaher Alghamdi, Yuqing Lin and Suhuai Luo
Efforts have been dedicated by researchers in the field of natural language processing (NLP) to detecting and combating fake news using an assortment of machine learning (ML) and deep learning (DL) techniques. In this paper, a review of the existing stud...
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Changsong Bing, Yirong Wu, Fangmin Dong, Shouzhi Xu, Xiaodi Liu and Shuifa Sun
Social media has become more popular these days due to widely used instant messaging. Nevertheless, rumor propagation on social media has become an increasingly important issue. The purpose of this study is to investigate the impact of various features i...
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Asma Baccouche, Begonya Garcia-Zapirain, Cristian Castillo Olea and Adel Elmaghraby
Heart diseases are highly ranked among the leading causes of mortality in the world. They have various types including vascular, ischemic, and hypertensive heart disease. A large number of medical features are reported for patients in the Electronic Heal...
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