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Titlebook: Web and Big Data; 7th International Jo Xiangyu Song,Ruyi Feng,Geyong Min Conference proceedings 2024 The Editor(s) (if applicable) and The

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21#
發(fā)表于 2025-3-25 03:21:06 | 只看該作者
,Truth Discovery Against Disguised Attack Mechanism in?Crowdsourcing,moid function. In the task allocation phase, the Weighted Arithmetic Mean (WAM) is used to estimate the allocation probability of golden tasks to avoid the shortage of golden tasks. Extensive experiments on real-world datasets and synthetic datasets demonstrate that our method is effective against d
22#
發(fā)表于 2025-3-25 10:28:32 | 只看該作者
Distributed Knowledge Graph Query Acceleration Algorithm, phase, which does not achieve good parallelism. To address these issues, we propose a distributed framework for offline index construction and online SPARQL query processing framework to achieve parallel accelerated processing. Our approach can more efficiently filter candidate solutions that do no
23#
發(fā)表于 2025-3-25 15:17:00 | 只看該作者
,Truth Discovery of?Source Dependency Perception in?Dynamic Scenarios,in dynamic scenarios, and propose an incremental model based on source dependency detection, namely SDPTD, which can dynamically update object truth values and source weights and detect source dependencies when new data arrive. Experiments on two real-world datasets and synthetic datasets demonstrat
24#
發(fā)表于 2025-3-25 18:35:36 | 只看該作者
25#
發(fā)表于 2025-3-25 22:47:47 | 只看該作者
,Approximate Continuous Skyline Queries over?Memory Limitation-Based Streaming Data,-adaptive .rror-based .pproximate .kyline). It can self-adaptively adjust . based on the distribution of streaming data, and achieve the goal of supporting .-. over memory limitation-based streaming data. Theoretical analysis indicates that even in the worst case, both the running cost and space cos
26#
發(fā)表于 2025-3-26 01:52:04 | 只看該作者
27#
發(fā)表于 2025-3-26 04:30:59 | 只看該作者
,Identifying Backdoor Attacks in?Federated Learning via?Anomaly Detection,nts. Concretely, we first segment the model gradients into fragment vectors that represent small portions of model parameters. We then employ anomaly detection to locate the distributionally skewed fragments and prune the participants with the most outliers. We embody the findings in a novel defense
28#
發(fā)表于 2025-3-26 10:43:34 | 只看該作者
29#
發(fā)表于 2025-3-26 16:12:46 | 只看該作者
,Approximate Continuous Skyline Queries over?Memory Limitation-Based Streaming Data,-adaptive .rror-based .pproximate .kyline). It can self-adaptively adjust . based on the distribution of streaming data, and achieve the goal of supporting .-. over memory limitation-based streaming data. Theoretical analysis indicates that even in the worst case, both the running cost and space cos
30#
發(fā)表于 2025-3-26 19:46:49 | 只看該作者
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