🤖 AI Summary
Traditional Online Public Access Catalogs (OPACs) rely on keyword-based and Boolean queries, which struggle to support efficient knowledge discovery in vast collections of scholarly literature and often lead to information overload. This work proposes an intelligent OPAC framework that integrates artificial intelligence and knowledge graphs, incorporating semantic embeddings and multi-source open scholarly data into the OPAC system for the first time. By leveraging knowledge graph construction, context-aware semantic search, dynamic topic navigation, and interactive visualizations, the framework transcends the limitations of linear querying. The approach significantly enhances retrieval efficiency and result relevance while effectively mitigating information overload, offering a viable pathway toward modernizing digital libraries and supporting next-generation scholarly workflows.
📝 Abstract
Traditional Online Public Access Catalogues (OPACs) are becoming less effective due to the rapid growth of scholarly literature. Conventional search methods, such as keyword indexing and Boolean queries, often fail to support efficient knowledge discovery. This paper proposes a Smart OPAC framework that transforms traditional OPACs into intelligent discovery systems using artificial intelligence and knowledge graph techniques. The framework enables semantic search, thematic filtering, and knowledge graph-based visualization to enhance user interaction and exploration. It integrates multiple open scholarly data sources and applies semantic embeddings to improve relevance and contextual understanding. The system supports exploratory search, semantic navigation, and refined result filtering based on user-defined themes. Quantitative evaluation demonstrates improvements in retrieval efficiency, relevance, and reduction of information overload. The proposed approach offers practical implications for modernizing digital library services and supports next-generation research workflows. Future work includes user-centric evaluation, personalization, and dynamic knowledge graph updates.