Knowledge Management Referral System Using Artificial Intelligent Techniques

Abstract

Knowledge management is an emerging area which is gaining interest from organization and governments. As moving nowadays toward building organizational knowledge, knowledge management will play a fundamental role towards the success of transforming tacit knowledge into organizational explicit knowledge during current big data and high level of competencies between organizations to provide promptly and required services. One of the key building blocks for developing and advancing this field of knowledge management is artificial intelligence. organizations need to be able to exchange information, queries, and requests with some other beneficiaries and agencies that they share a common unified domain. One possible approach to this issue is Automating Knowledge, the methods which have been used to employ Semantic techniques for modeling about provide automatic accurate information extracts inquiry’s answer from the proposed knowledge management system. This paper will clarify the future of knowledge management system and the methodology of its link to artificial intelligence in organizations when it’s come to providing humanitarian emergency assistant, services and health care as the current global pandemic virus. The advanced proposed system will enable beneficiaries, employees and external official entities to get instantly automatically replay for various inquiries without required humanitarian intervention unless it's necessary! and enable to save ’ transfer ’ retrieve and generate new knowledge through three levels depending on the semantic technique, natural language processing algorithms and Ontology techniques in extracting inquiry’s answer in the first level then using chat system with an employee in the second level and through sending email to the specialist in the last third level. The validity of the method is proved in this comprehensive intelligent inquiry system. Showing the effectiveness of this approach by testing it on a humanitarian agency. The experimental results were extremely encouraging as such organization did not own automatic knowledge management system as its provisions on this research paper, so its recommended to use it in a large area as the proposed system show outperforms baseline methods and improve the accuracy answering by 86%.