Semantic matching based legal information retrieval system for COVID-19 pandemic

IF 3.1 2区社会学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

Artificial Intelligence and Law Pub Date : 2023-03-14 DOI:10.1007/s10506-023-09354-x

Junlin Zhu, Jiaye Wu, Xudong Luo, Jie Liu

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引用次数: 0

Abstract

Recently, the pandemic caused by COVID-19 is severe in the entire world. The prevention and control of crimes associated with COVID-19 are critical for controlling the pandemic. Therefore, to provide efficient and convenient intelligent legal knowledge services during the pandemic, we develop an intelligent system for legal information retrieval on the WeChat platform in this paper. The data source we used for training our system is “The typical cases of national procuratorial authorities handling crimes against the prevention and control of the new coronary pneumonia pandemic following the law”, which is published online by the Supreme People’s Procuratorate of the People’s Republic of China. We base our system on convolutional neural network and use the semantic matching mechanism to capture inter-sentence relationship information and make a prediction. Moreover, we introduce an auxiliary learning process to help the network better distinguish the relation between two sentences. Finally, the system uses the trained model to identify the information entered by a user and responds to the user with a reference case similar to the query case and gives the reference legal gist applicable to the query case.

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基于语义匹配的新冠肺炎疫情法律信息检索系统。

最近，新冠肺炎引起的疫情在全世界都很严重。预防和控制与新冠肺炎有关的犯罪对于控制这一流行病至关重要。因此，为了在疫情期间提供高效便捷的智能法律知识服务，本文开发了一个在微信平台上进行法律信息检索的智能系统。我们用于培训系统的数据源是中华人民共和国最高人民检察院在线发布的“全国检察机关依法处理危害新型冠状病毒肺炎疫情防控犯罪的典型案例”。我们的系统基于卷积神经网络，并使用语义匹配机制来捕获句间关系信息并进行预测。此外，我们引入了一个辅助学习过程来帮助网络更好地区分两句之间的关系。最后，该系统使用经过训练的模型来识别用户输入的信息，并用与查询案例类似的参考案例来响应用户，并给出适用于查询案例的参考法律依据。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Artificial Intelligence and Law Multiple-

CiteScore

9.50

自引率

26.80%

发文量

期刊介绍： Artificial Intelligence and Law is an international forum for the dissemination of original interdisciplinary research in the following areas: Theoretical or empirical studies in artificial intelligence (AI), cognitive psychology, jurisprudence, linguistics, or philosophy which address the development of formal or computational models of legal knowledge, reasoning, and decision making. In-depth studies of innovative artificial intelligence systems that are being used in the legal domain. Studies which address the legal, ethical and social implications of the field of Artificial Intelligence and Law. Topics of interest include, but are not limited to, the following: Computational models of legal reasoning and decision making; judgmental reasoning, adversarial reasoning, case-based reasoning, deontic reasoning, and normative reasoning. Formal representation of legal knowledge: deontic notions, normative modalities, rights, factors, values, rules. Jurisprudential theories of legal reasoning. Specialized logics for law. Psychological and linguistic studies concerning legal reasoning. Legal expert systems; statutory systems, legal practice systems, predictive systems, and normative systems. AI and law support for legislative drafting, judicial decision-making, and public administration. Intelligent processing of legal documents; conceptual retrieval of cases and statutes, automatic text understanding, intelligent document assembly systems, hypertext, and semantic markup of legal documents. Intelligent processing of legal information on the World Wide Web, legal ontologies, automated intelligent legal agents, electronic legal institutions, computational models of legal texts. Ramifications for AI and Law in e-Commerce, automatic contracting and negotiation, digital rights management, and automated dispute resolution. Ramifications for AI and Law in e-governance, e-government, e-Democracy, and knowledge-based systems supporting public services, public dialogue and mediation. Intelligent computer-assisted instructional systems in law or ethics. Evaluation and auditing techniques for legal AI systems. Systemic problems in the construction and delivery of legal AI systems. Impact of AI on the law and legal institutions. Ethical issues concerning legal AI systems. In addition to original research contributions, the Journal will include a Book Review section, a series of Technology Reports describing existing and emerging products, applications and technologies, and a Research Notes section of occasional essays posing interesting and timely research challenges for the field of Artificial Intelligence and Law. Financial support for the Journal of Artificial Intelligence and Law is provided by the University of Pittsburgh School of Law.