{"id":12953,"date":"2026-10-09T14:31:07","date_gmt":"2026-10-09T06:31:07","guid":{"rendered":"\/jase\/?post_type=tkuisotope&p=12953"},"modified":"2026-10-09T21:53:31","modified_gmt":"2026-10-09T13:53:31","slug":"jase-202701-36-013","status":"publish","type":"tkuisotope","link":"\/jase\/?tkuisotope=jase-202701-36-013","title":{"rendered":"Secure Knowledge Graph Construction and PrivacyPreserving Question Answering for Industrial Knowledge Service-Oriented Distributed Digital Libraries"},"content":{"rendered":"\n
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<\/i> 2027<\/a><\/p>\n<\/div>\n\n\n\n

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<\/i> Volume 36<\/a><\/p>\n<\/div>\n\n\n\n

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Jin Li<\/i><\/a><\/p>\n\n\n\n

Changsha Commerce & Tourism College, Changsha, 410116, China<\/p>\n<\/div>\n\n\n\n

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Received: July 21, 2026
Accepted: August 14, 2026
Publication Date: October 09, 2026<\/p>\n<\/div>\n<\/div>\n\n\n\n

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Overall system architecture of the proposed industrial knowledge service-oriented distributed digital library framework <\/p>\n<\/div>\n<\/div>\n\n\n\n

<\/i> Copyright <\/strong>The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0)<\/a>, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are cited.<\/p>\n\n\n\n

Download Citation: BibTeX <\/a>| http:\/\/dx.doi.org\/10.6180\/jase.202701_36.013<\/a> <\/p>\n\n\n\n

Download PDF<\/a><\/p>\n\n\n\n

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Industrial knowledge service-oriented distributed digital libraries integrate patents, standards, drawings, reports, and bibliographic records across nodes, facing collection fusion, entity redundancy, privacy leakage, and limited QA scalability. This study proposes a secure knowledge graph construction and privacy-preserving QA method combining metadata standardization, entity extraction, relation recognition, cross-library alignment, credibility-driven triple verification, graph partitioning, hotspot caching, parallel retrieval, and differential privacy ranking[cite: 108]. Evaluated at five scales, it reaches 94.2%\/92.6%\/94.5%\/93.1% entity F1\/relation F1\/alignment accuracy\/triple validity, and QA accuracy\/F1\/MRR\/Hit@5 of 93.6%\/92.1%\/91.3%\/95.2%. At 64 nodes, latency is 360 ms (vs. 950\/1650 ms for Federated\/Centralized KG-QA), with 1650 queries\/s at 10,000 concurrent queries.<\/p>\n\n\n\n

Keywords: Industrial knowledge service, distributed digital library, secure knowledge graph, privacy-preserving question answering, entity alignment, differential privacy<\/em><\/p>\n\n\n\n

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