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Titlebook: Database and Expert Systems Applications; 32nd International C Christine Strauss,Gabriele Kotsis,Ismail Khalil Conference proceedings 2021

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發(fā)表于 2025-3-26 23:25:32 | 只看該作者
32#
發(fā)表于 2025-3-27 03:18:43 | 只看該作者
33#
發(fā)表于 2025-3-27 07:33:52 | 只看該作者
Towards New Model for Handling Inconsistency Issues in DL-Lite Knowledge?Basesin the framework of this work, and the main algorithms studied in the literature. The results obtained show that our algorithm is more productive than the others, compared to standard performance measures, namely precision, recall and F-measure.
34#
發(fā)表于 2025-3-27 10:33:54 | 只看該作者
35#
發(fā)表于 2025-3-27 17:16:38 | 只看該作者
Less is More: Feature Choosing under Privacy-Preservation for Efficient Web Spam Detections paper, a cascade feature selection for mining spam is proposed, which bases on Privacy Preservation (PP) method and Genetic Algorithm (GA). Two criteria, privacy protection degree and maximum classification reliability, are used to pick the representative features to form an optimal minimum featur
36#
發(fā)表于 2025-3-27 21:30:09 | 只看該作者
Construction of Differentially Private Summaries Over Fully Homomorphic Encryption. proposed Cryptε, which executes differential privacy (DP) over encrypted data on two non-colluding semi-honest servers. Further, the DP index proposed by these authors summarizes a dataset to prevent information leakage while improving the performance. However, two problems persist: 1) the origina
37#
發(fā)表于 2025-3-27 23:19:46 | 只看該作者
SafecareOnto: A Cyber-Physical Security Ontology for Healthcare Systemss are triggered, leading to many high-impact incidents. There is a growing need for innovative solutions that combine cyber and physical security features. To improve the response to incidents caused by attacks combining cyber and physical threats, we have produced within the H2020 project “Safecare
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發(fā)表于 2025-3-28 04:40:22 | 只看該作者
39#
發(fā)表于 2025-3-28 08:17:08 | 只看該作者
40#
發(fā)表于 2025-3-28 10:35:12 | 只看該作者
NV-QALSH: An NVM-Optimized Implementation of Query-Aware Locality-Sensitive Hashinghods are either DRAM-based ones which consume a vast amount of expensive DRAM and are time-consuming to rebuild after programs reboot, or disk-based ones such as the state-of-the-art QALSH (Query-Aware LSH), which suffers from high latency of disk I/O. In this paper, we find that the emerging non-vo
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