论文标题
自动智能助手的语义网络框架:covid-19案例研究
A Semantic Web Framework for Automated Smart Assistants: COVID-19 Case Study
论文作者
论文摘要
COVID-19大流行阐明,在需要将准确信息传达给具有不同背景和技术资源的大量人群的情况下,知识系统将有助于。但是,一些挑战和障碍阻碍了公共卫生部门和组织对虚拟助手的广泛采用。本文介绍了即时专家,这是一个开源的语义网络框架,可为任何网络平台构建和集成支持语音的智能助手(即聊天机器人),而不论基础域和技术如何。该组件允许非技术领域专家轻松地将具有语音识别能力的运营助理纳入其网站。 Instant Expert能够自动解析,处理和建模常见问题页面作为信息资源,并与外部知识引擎进行沟通,以进行本体论的推理和动态数据利用。提出的框架利用先进的Web技术来确保可重复性和可靠性,以及由深度学习和启发式算法提供支持的自然语言理解的推理引擎。提出了一种基于疾病控制和预防中心(CDC)数据为Covid-19创建信息助理的用例,以证明框架的使用和福利。
COVID-19 pandemic elucidated that knowledge systems will be instrumental in cases where accurate information needs to be communicated to a substantial group of people with different backgrounds and technological resources. However, several challenges and obstacles hold back the wide adoption of virtual assistants by public health departments and organizations. This paper presents the Instant Expert, an open-source semantic web framework to build and integrate voice-enabled smart assistants (i.e. chatbots) for any web platform regardless of the underlying domain and technology. The component allows non-technical domain experts to effortlessly incorporate an operational assistant with voice recognition capability into their websites. Instant Expert is capable of automatically parsing, processing, and modeling Frequently Asked Questions pages as an information resource as well as communicating with an external knowledge engine for ontology-powered inference and dynamic data utilization. The presented framework utilizes advanced web technologies to ensure reusability and reliability, and an inference engine for natural language understanding powered by deep learning and heuristic algorithms. A use case for creating an informatory assistant for COVID-19 based on the Centers for Disease Control and Prevention (CDC) data is presented to demonstrate the framework's usage and benefits.