Devine Samuel Nii Odoi, Kolog Emmanuel Awuni, Atinga Roger
Department of Information and Communication Technology, Presbyterian University College, Abetifi, Ghana.
Department of Operations and Management Information Systems, University of Ghana, Accra, Ghana.
Front Artif Intell. 2022 Mar 9;5:856705. doi: 10.3389/frai.2022.856705. eCollection 2022.
This article illustrates a design approach for capturing, storing, indexing, and search of African traditional herbal medicine (ATHMed) framed on a hybrid-based knowledge model for efficient preservation and retrieval. By the hybrid approach, the framework was developed to include both the use of machine learning and ontology-based techniques. The search pattern considers ontology design and machine learning techniques for extracting ATHMed data. The framework operates on a semantically annotated corpus and delivers a contextual and multi-word search pattern against its knowledge base. In line with design science research, preliminary data were collected in this study, and a proposed strategy was developed toward processing, storing and retrieving data. While reviewing literature and interview data to reflect on the existing challenges, these findings suggest the need for a system with the capability of retrieving and archiving ATHMed in Ghana. This study contributes to SDG 3 by providing a model and conceptualizing the implementation of ATHMed. We, therefore, envision that the framework will be adopted by relevant stakeholders for the implementation of efficient systems for archival and retrieval of ATHMed.
本文阐述了一种基于混合知识模型的非洲传统草药(ATHMed)的捕获、存储、索引和搜索设计方法,以实现高效保存和检索。通过混合方法,该框架被开发为同时使用机器学习和基于本体的技术。搜索模式考虑了本体设计和机器学习技术来提取ATHMed数据。该框架在语义标注语料库上运行,并针对其知识库提供上下文和多词搜索模式。根据设计科学研究,本研究收集了初步数据,并制定了一种用于处理、存储和检索数据的策略。在回顾文献和访谈数据以反思现有挑战时,这些发现表明需要一个能够在加纳检索和存档ATHMed的系统。本研究通过提供一个模型并将ATHMed的实施概念化,为可持续发展目标3做出了贡献。因此,我们设想该框架将被相关利益攸关方采用,以实施高效的ATHMed存档和检索系统。