Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 40, 2023 No. 8
2393-2398

Multi-turn dialogue response selection model based on deep multi-matching network

Liu Chao
Li Wan
School of Computer Science & Engineering, Chongqing University of Technology, Chongqing 400054, China
DOI: 10.19734/j.issn.1001-3695.2022.11.0783

Abstract

There are still issues with insufficient model information screening that introduces noise, insufficient mining of potential semantic information, and insufficient consideration of the temporal relationships of known contents, although existing works have constructed a variety of retrieval models using neural networks with some success. The research suggested a multi-turn dialogue response model based on a deep multi-matching network(DMMN) to overcome the aforementioned problems. The model took context and knowledge as queries to candidate responses, proposed a pre-matching layer after encoding all three, and used a one-way cross-attention mechanism to filter knowledge-aware context and context-aware knowledge, respectively, to identify the important information in both. After the candidate response had interacted with the aforementioned two, it conducted a feature aggregation phase to improve the matching feature information by mining the semantic information between the response-based knowledge and the attention mechanism with gating on the one hand and the temporal information between the response-based contextual dialogue messages with the aid of an additional BiLSTM network on the others. Finally, the representation features mentioned above were combined. According to the performance evaluation results on the original and revised Persona-Chat datasets, the model has further increased the recall rate and recovered better responses when compared to existing approaches.

Foundation Support

国家教育考试科研规划课题(GJK2019006)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2022.11.0783
Publish at: Application Research of Computers Printed Article, Vol. 40, 2023 No. 8
Section: Algorithm Research & Explore
Pages: 2393-2398
Serial Number: 1001-3695(2023)08-023-2393-06

Publish History

[2023-02-27] Accepted Paper
[2023-08-05] Printed Article

Cite This Article

刘超, 李婉. 基于深度多匹配网络的多轮对话回复选择模型 [J]. 计算机应用研究, 2023, 40 (8): 2393-2398. (Liu Chao, Li Wan. Multi-turn dialogue response selection model based on deep multi-matching network [J]. Application Research of Computers, 2023, 40 (8): 2393-2398. )

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  • 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.

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