【目的/意義】大數據背景下,優良的多媒體信息檢索系統是提升數字圖書館交互性,促使其知識服務升級的關鍵。【方法/過程】調研主流數字圖書館的多媒體信息檢索系統,發現主要存在"未充分利用跨模態相關性"、"未有效組織多媒體資源"等問題。從"跨模態相關性分析"、"層次化知識推理"等方面提出優化方案并實證分析。【結果/結論】系統檢索性能提升,這表明:運用深度學習、知識表示學習等理論優化多媒體信息檢索系統,可更好地滿足用戶知識需求,進而提升數字圖書館知識服務質量。

【Purpose/significance】Under the big data environment, a better multi-media information retrieval system is one of the core aspects for promoting digital libraries’ interactivities and impelling the transformation of its knowledge services.【Method/process】After investigating several famous digital libraries, it finds out two key problems still remain in the traditional multi-media retrieval system. The first is"the useful cross-modal semantic information wasn’t applied in the retriev-al procedure". The second is"the multi-media resources in digital library weren’t organized and managed systematically".To resolve the problems and improve retrieval performance in some extent, it proposes several novel ideas for optimizing thetraditional multi-media information retrieval system:"cross-modal correlation analysis","hierarchical knowledge reasoning", et al. Detailed empirical analysis is done to verify the presented novel ideas.【Result/conclusion】Retrieval performances are improved apparently. It means that several modern technologies such as deep learning and knowledge represen-tation learning actually contribute to optimize the traditional multi-media information retrieval system of digital library.More importantly, it can better satisfy users’ knowledge demands and improve the knowledge service quality of digital library.