Integrating Semantic Web, Artificial Intelligence, and Knowledge Management for Enhanced Accounting in SMEs

Abstract

This study explores the integration of Semantic Web (SW), Artificial Intelligence (AI), and Knowledge Management (KM) to improve accounting practices in small and medium-sized enterprises (SMEs). Recognizing the challenges SMEs face in managing accounting knowledge due to insufficient expertise and fragmented data sources, this research proposes a conceptual model that utilizes SW technologies, such as Resource Description Framework (RDF) and Web Ontology Language (OWL), to create a unified ontology for diverse accounting information. By leveraging AI techniques, including machine learning and natural language processing, the model aims to enhance knowledge retrieval, ontology enrichment, and case-based reasoning, facilitating more efficient and accurate accounting knowledge management. The findings highlight the potential of this integrated approach to support online training, decision-making, and overall competitiveness of SMEs, addressing the limitations of traditional accounting practices. The study concludes with recommendations for further research to refine the integration of SW, AI, and KM in accounting.