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App. Res. of Comp. Accepted Paper
Vol. 41, 2024 No. 12

Joint recognition algorithm of intents and semantic slots for human-machine dialogue in industrial operation and maintenance

Zhou Chao1
Wang Cheng1
Xia Yuan2
Du Lin2
1. School of Internet of Things, Jiangnan University, Wuxi Jiangsu 214122, China
2. Jiangyin Yiyuan-Jiangnan University Joint Laboratory of Industrial Intelligent Maintenance, Wuxi Jiangsu 214400, China
DOI: 10.19734/j.issn.1001-3695.2024.06.0148

Abstract

Intent recognition and slot filling aim to determine intent and extract key information slots, which are the keys to realizing human-machine dialogue. In the task of human-machine dialogue for industrial operation and maintenance, in order to solve problems such as complex nested entities, missing words and typos in the data, this paper proposed an improved BERT joint algorithm GP-GraphBERT, which used the correlation of intent and semantic slot recognition to improve dialogue performance. First, after obtaining the hidden layer states from BERT, constructed an adjacency matrix to convert them into a graph structure and embedded it into WRGAT to enhance the model's neighbor-awareness capabilities. Secondly, the algorithm improved the GlobalPointer mechanism incorporating RoPE, enabling the model to uniformly recognize both regular and nested entities. Finally, designed a joint loss function for intent recognition and semantic slot recognition tasks, leveraging their correlation to improve prediction accuracy. During model training, introduced dynamic masking to enhance the model's robustness and generalization capabilities. Experimental results showed F1 scores of GP-GraphBERT algorithm achieved 87.5% and 86.4% for intent recognition and semantic slot recognition on the industrial operation and maintenance human-machine dialogue datasets, which were respectively improved by 9.2% and 3.0% compared to the original network, while also met the requirements for nested entity identification. The experiments fully verifies the performance of the algorithm in the joint recognition task.

Foundation Support

近地面探测技术重点实验室基金项目(6142414220203)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2024.06.0148
Publish at: Application Research of Computers Accepted Paper, Vol. 41, 2024 No. 12

Publish History

[2024-09-09] Accepted Paper

Cite This Article

周超, 王呈, 夏源, 等. 面向工业运维人机对话的意图和语义槽联合识别算法 [J]. 计算机应用研究, 2024, 41 (12). (2024-09-11). https://doi.org/10.19734/j.issn.1001-3695.2024.06.0148. (Zhou Chao, Wang Cheng, Xia Yuan, et al. Joint recognition algorithm of intents and semantic slots for human-machine dialogue in industrial operation and maintenance [J]. Application Research of Computers, 2024, 41 (12). (2024-09-11). https://doi.org/10.19734/j.issn.1001-3695.2024.06.0148. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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