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作者:

Yao, Yahong (Yao, Yahong.) | Lin, Shaofu (Lin, Shaofu.) | Huang, Zhisheng (Huang, Zhisheng.) | Li, Shushi (Li, Shushi.) | Guo, Chaohui (Guo, Chaohui.) | Wu, Ying (Wu, Ying.)

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EI Scopus

摘要:

Purpose: Traditional psychological crisis intervention requires one-to-one and long-term consultation by psychotherapists, which has high time cost and expense. The public has a strong realistic demand for more convenient psychological crisis intervention services. In order to solve the above problem, this paper presents an approach which transforms the actual professional psychological consultation data into knowledge graph, establishes a terminology/ontology of psychological crisis intervention, and constructs an automatic service prototype system of psychological crisis intervention. Method: This paper takes actual professional psychological crisis intervention cases as prior knowledge, expresses and stores them in the form of triples. The natural language generation model based on GPT-2 model is constructed by using the data in PsyQA as the training set for several rounds of training. The terminology of psychological crisis intervention is constructed. Then the psychological crisis intervention system is constructed, including modules as keyword extraction, deep semantic matching, knowledge graph retrieval crisis intervention strategy providing module and natural language generation. Result: The test results show that for the users which can correctly input the psychological problem description text, the system can Identify crisis types, provide the corresponding intervention strategies and return the targeted crisis intervention text. Conclusion: This system avoids the constraints of traditional crisis intervention such as high price, poor timeliness and few professionals, and provides a feasible method for people who need to get simple crisis intervention services in time. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词:

Terminology Natural language processing systems Knowledge graph Semantics

作者机构:

  • [ 1 ] [Yao, Yahong]Faculty of Information Technology, Beijing University of Technology, Beijing, China
  • [ 2 ] [Lin, Shaofu]Faculty of Information Technology, Beijing University of Technology, Beijing, China
  • [ 3 ] [Huang, Zhisheng]Department of Computer Science, Vrije University Amsterdam, Amsterdam, Netherlands
  • [ 4 ] [Li, Shushi]Faculty of Information Technology, Beijing University of Technology, Beijing, China
  • [ 5 ] [Guo, Chaohui]Faculty of Information Technology, Beijing University of Technology, Beijing, China
  • [ 6 ] [Wu, Ying]Faculty of Information Technology, Beijing University of Technology, Beijing, China

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ISSN: 0302-9743

年份: 2022

卷: 13705 LNCS

页码: 209-216

语种: 英文

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