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6 May 2022 A hybrid Chinese named entity recognition method for Internet of Things
Ying Wang, Zehao Wang, Hong Li, Yachao Li, Fang Zuo
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Proceedings Volume 12176, International Conference on Algorithms, Microchips and Network Applications; 121762A (2022) https://doi.org/10.1117/12.2636480
Event: International Conference on Algorithms, Microchips, and Network Applications 2022, 2022, Zhuhai, China
Abstract
In order to facilitate government departments to assess security risks and prevent infiltration, it’s necessary to recognize the IoT device from open data by the method of Named entity recognition (NER). In this study, a hybrid method of chinese NER which contains neural networks and templates is proposed to extract IoT device information from open web. The model first initiates characters of input through BERT, which can create character embedding while reduce dependency with external datasets. Then, the initiated vectors are fed into a multi-layers BiLSTM model to encode the contextual representation of each character, and a linear CRF layer after BiLSTM is used to assign the scores to every character for entity annotation. In addition, a dictionary and rule base is constructed based on the characteristics of IoT devices to correct the annotation results. We experimented the methods on the dataset of IoT, the results prove the proposed model achieves better recognition effect than other models, and the F-scores value is 88.9%.
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Ying Wang, Zehao Wang, Hong Li, Yachao Li, and Fang Zuo "A hybrid Chinese named entity recognition method for Internet of Things", Proc. SPIE 12176, International Conference on Algorithms, Microchips and Network Applications, 121762A (6 May 2022); https://doi.org/10.1117/12.2636480
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KEYWORDS
Internet
Data modeling
Computer programming
Information security
Network security
Transformers
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