Article: Development of a unified digital library system: integration of image processing, big data, and deep learning Journal: International Journal of Information and Communication Technology (IJICT) 2024 Vol.24 No.3 pp.378 - 391 Abstract: The digital library serves as a multifaceted information hub, housing text, sound, images, video, and literature in digital form. It aids users with retrieval, download, and document transfer services. Amidst big data, a robust multimedia retrieval system is pivotal for enhancing digital library interactions and knowledge services. This paper delves into the amalgamation of image processing, big data, and deep learning for digital library integration. By analysing deep learnings concept, structure, and semantic search relations, it identifies issues like under-utilising cross-modal correlation and insufficient multimedia resource organisation. Proposing a cross-media semantic search framework for digital libraries rooted in deep learning, the study suggests optimisation strategies involving cross-modal correlation analysis and hierarchical knowledge inference. The implemented Pillar+Spring+Sleep method demonstrates an 11.53% improvement in overall search performance over the suboptimal index. This optimised scheme seeks to refine and advance multimedia retrieval systems within digital libraries, especially in managing the vast yet imprecise media data of the big data era. Inderscience Publishers - linking academia, business and industry through research

Title: Development of a unified digital library system: integration of image processing, big data, and deep learning

Authors: Xiaoyan Wang; Meimei Jia

Addresses: School of Computer Science and Technology, Nanyang Normal University, Nanyang, Henan, 473061, China ' School of Computer Science and Technology, Nanyang Normal University, Nanyang, Henan, 473061, China

Abstract: The digital library serves as a multifaceted information hub, housing text, sound, images, video, and literature in digital form. It aids users with retrieval, download, and document transfer services. Amidst big data, a robust multimedia retrieval system is pivotal for enhancing digital library interactions and knowledge services. This paper delves into the amalgamation of image processing, big data, and deep learning for digital library integration. By analysing deep learnings concept, structure, and semantic search relations, it identifies issues like under-utilising cross-modal correlation and insufficient multimedia resource organisation. Proposing a cross-media semantic search framework for digital libraries rooted in deep learning, the study suggests optimisation strategies involving cross-modal correlation analysis and hierarchical knowledge inference. The implemented Pillar+Spring+Sleep method demonstrates an 11.53% improvement in overall search performance over the suboptimal index. This optimised scheme seeks to refine and advance multimedia retrieval systems within digital libraries, especially in managing the vast yet imprecise media data of the big data era.

Keywords: digital library; information integration; big data; deep learning; multimedia retrieval system.

DOI: 10.1504/IJICT.2024.137942

International Journal of Information and Communication Technology, 2024 Vol.24 No.3, pp.378 - 391

Received: 20 Nov 2023
Accepted: 17 Dec 2023
Published online: 11 Apr 2024 *

Title: Development of a unified digital library system: integration of image processing, big data, and deep learning

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