標題: Titlebook: Database Systems for Advanced Applications; 28th International C Xin Wang,Maria Luisa Sapino,Hongzhi Yin Conference proceedings 2023 The Ed [打印本頁] 作者: 孵化 時間: 2025-3-21 18:57
書目名稱Database Systems for Advanced Applications影響因子(影響力)
書目名稱Database Systems for Advanced Applications影響因子(影響力)學(xué)科排名
書目名稱Database Systems for Advanced Applications網(wǎng)絡(luò)公開度
書目名稱Database Systems for Advanced Applications網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Database Systems for Advanced Applications被引頻次
書目名稱Database Systems for Advanced Applications被引頻次學(xué)科排名
書目名稱Database Systems for Advanced Applications年度引用
書目名稱Database Systems for Advanced Applications年度引用學(xué)科排名
書目名稱Database Systems for Advanced Applications讀者反饋
書目名稱Database Systems for Advanced Applications讀者反饋學(xué)科排名
作者: 擺動 時間: 2025-3-21 23:33
https://doi.org/10.1007/978-3-031-30678-5Query Processing; Data Management; Graph; Network; Knowledge Graph作者: 挖掘 時間: 2025-3-22 03:41
978-3-031-30677-8The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl作者: 猜忌 時間: 2025-3-22 05:45
Christian Masiak,Alexandra Moritz,Frank Langt of the existing approaches can hardly model complicated contexts since they fail to use dependency-type knowledge in texts to assist in identifying implicit clues to event relations, leading to the sub-optimal performance on this task. To this end, we propose a novel type-guided attentive graph co作者: Mosaic 時間: 2025-3-22 12:31 作者: ENACT 時間: 2025-3-22 13:54
Contemporary Ecology Research in Chinaticles into events and connect related events in growing trees to generate storylines. Unfortunately, these methods did not perform well in learning the implicit associations of events. More recently, Graph Convolutional Network (GCN) based methods are proposed to learn the implicit associations bet作者: ENACT 時間: 2025-3-22 18:13 作者: caldron 時間: 2025-3-22 22:37 作者: 小爭吵 時間: 2025-3-23 03:10 作者: 外露 時間: 2025-3-23 07:56
Corporate Ethics and Management Theoryning has been used in UDA, which exploits pseudo-labels for unlabeled target domains. However, the pseudo-labels can be unreliable due to distribution shifts between domains, severely impairing the model performance. To address this problem, we propose a novel self-training framework-Self-Training w作者: CHASE 時間: 2025-3-23 11:03
Masahisa Fujita,Jacques-Fran?ois Thisseat the unlabeled set as a substitute for normal samples and ignore the potential anomalies in it, which fails make full use of the abnormal supervision information. To address this issue, we propose a .eta-.seudo-label based framework for .nomaly .etection (MPAD). The framework strives to obtain eff作者: ARCH 時間: 2025-3-23 14:18
Masahisa Fujita,Jacques-Fran?ois Thisseto detect outliers in more than two views. Moreover, they only employ the clustering technique to detect outliers in a multi-view scenario. Besides, the relationships among different views are not fully utilized. To address the above issues, we propose ECMOD for learning .nhanced representations via作者: Canyon 時間: 2025-3-23 18:48
Yair Mundlak,Donald Larson,Al Cregoe performance, their performance drops dramatically when adapting to the new domain and under few-shot scenarios. One reason is that the huge gap in semantic space between different domains makes the model obtain suboptimal representations in the new domain. The other is the inability to learn class作者: antidepressant 時間: 2025-3-24 01:03 作者: adulterant 時間: 2025-3-24 03:57
Timothy M. Smeeding,Peter Gottschalkty and improving user experience in a task-oriented dialogue system. The key challenge is how to learn discriminative intent representations that are beneficial for distinguishing in-domain (IND) and OOD intents. However, previous methods ignore the compactness between instances and dispersion among作者: 全神貫注于 時間: 2025-3-24 06:55
https://doi.org/10.1007/978-1-349-26188-8ot all data owners (or keepers) could develop feasible learning models for knowledge discovery’s sake. Oftentimes, the original data need to be passed to or shared with researchers or data scientists for better mining insights, especially in the medical, financial, and industrial fields. However, co作者: eustachian-tube 時間: 2025-3-24 11:09 作者: 遺傳學(xué) 時間: 2025-3-24 15:50
The Prehistory of Chaotic Economic Dynamicsls is becoming marginal. Instead, we argue that the improvement can be achieved by using traffic-related facts or laws, which is termed exogenous knowledge. To this end, we propose a knowledge-driven memory system that can be seamlessly integrated into GCN-based traffic forecasting models. Specifica作者: 無動于衷 時間: 2025-3-24 21:19 作者: coagulation 時間: 2025-3-24 23:36 作者: 專橫 時間: 2025-3-25 07:00 作者: HOWL 時間: 2025-3-25 10:52
Lecture Notes in Computer Sciencehttp://image.papertrans.cn/d/image/263427.jpg作者: dissolution 時間: 2025-3-25 14:18 作者: Statins 時間: 2025-3-25 15:58
PMJEE: A Prototype Matching Framework for?Joint Event Extractioncode their label semantics and correlations. Then a dual-channel attention layer and extraction modules are used to jointly extract event triggers and arguments. Prototypical embeddings will be optimized during training to improve the event extraction performance. Extensive experiments indicate our 作者: 元音 時間: 2025-3-25 22:26 作者: 付出 時間: 2025-3-26 02:45 作者: 過度 時間: 2025-3-26 07:31
Powering Fine-Tuning: Learning Compatible and?Class-Sensitive Representations for?Domain Adaption Ferent domains and obtain better representations. To enhance the stability and learning ability of contrastive learning-based fine-tuning, we design the data augmentation mechanism and type-aware networks to enrich the instances and stand out the class-sensitive features. Extensive experiments on the 作者: 頭腦冷靜 時間: 2025-3-26 10:42 作者: 不舒服 時間: 2025-3-26 14:50
Modeling Intra-class and?Inter-class Constraints for?Out-of-Domain Detection constraint contrastive learning (Inter-CCL) objective to effectively enlarge the discrepancy among different classes as much as possible, enforcing the strong separability for different classes in the intent embedding space. Besides, to further enhance the discriminative representation capability o作者: NUDGE 時間: 2025-3-26 20:45 作者: Minutes 時間: 2025-3-26 23:55
Rainfall Spatial Interpolation with?Graph Neural Networksractical rainfall interpolation well. To address these limitations, we propose a novel GSI (.raph for .patial .nterpolation) model, which focuses on learning the spatial message-passing mechanism. By constraining the message passing flow and adaptive graph structure learning, GSI can perform effecti作者: 瑪瑙 時間: 2025-3-27 03:06 作者: Perennial長期的 時間: 2025-3-27 05:36 作者: 預(yù)測 時間: 2025-3-27 11:25 作者: LIEN 時間: 2025-3-27 13:51
Adversarial Learning-Based Stance Classifier for?COVID-19-Related Health Policiesorporate policy descriptions as external knowledge into the model. Meanwhile, a GeoEncoder is designed which encourages the model to capture unobserved background factors specified by each region and then represent them as non-text information. We evaluate the performance of a broad range of baselin作者: 別名 時間: 2025-3-27 18:40
Christian Masiak,Alexandra Moritz,Frank Langegate semantic context among texts. Finally, the event relation is predicted based on the representations of event pair and the representation of the whole text, completing the task of event relation extraction. The experimental results on multiple datasets show that our method significantly outperf作者: obsolete 時間: 2025-3-27 23:00 作者: Cumulus 時間: 2025-3-28 03:30 作者: HACK 時間: 2025-3-28 07:33 作者: Ingrained 時間: 2025-3-28 10:43
Yair Mundlak,Donald Larson,Al Cregorent domains and obtain better representations. To enhance the stability and learning ability of contrastive learning-based fine-tuning, we design the data augmentation mechanism and type-aware networks to enrich the instances and stand out the class-sensitive features. Extensive experiments on the 作者: frugal 時間: 2025-3-28 15:12
W. Lieb Nieuwoudt,Graham Moor,Rupert Baberinto the LBF, and we provide the theoretical analysis to show their lower bound property and computational efficiency. Experimental results on various synthetic and real-world datasets demonstrate the effectiveness of the proposals compared with the baseline .-means++ seeding and approximate method.作者: omnibus 時間: 2025-3-28 21:37
Timothy M. Smeeding,Peter Gottschalk constraint contrastive learning (Inter-CCL) objective to effectively enlarge the discrepancy among different classes as much as possible, enforcing the strong separability for different classes in the intent embedding space. Besides, to further enhance the discriminative representation capability o作者: modest 時間: 2025-3-29 02:19
https://doi.org/10.1007/978-1-349-26188-8rs are combined to synthesize realistically distributed data. To demonstrate the feasibility of the model, we evaluated it from three aspects: how similar are the distributions of the synthetic data to the original data, how well can the synthetic data accomplish future data mining tasks, and how mu作者: originality 時間: 2025-3-29 03:48
International Economic Association Seriesractical rainfall interpolation well. To address these limitations, we propose a novel GSI (.raph for .patial .nterpolation) model, which focuses on learning the spatial message-passing mechanism. By constraining the message passing flow and adaptive graph structure learning, GSI can perform effecti作者: 泰然自若 時間: 2025-3-29 10:32
The Prehistory of Chaotic Economic Dynamicss achieved by constraining the learning process with unsupervised loss functions formulated inspired by exogenous knowledge. We construct three kinds of memory modules driven by different exogenous knowledge: the long-term trend memory to learn periodic patterns, the hierarchical effect memory to ca作者: Bravura 時間: 2025-3-29 14:27
https://doi.org/10.1007/978-1-349-14540-9 in the initial phase until the model is sufficiently trained and ready to use. Besides, to choose multiple actions simultaneously, we replace the actor’s output in standard reinforcement learning with a 2D matrix indicating the mixed feature representation of all different actions, then multiply it作者: 彩色的蠟筆 時間: 2025-3-29 16:06
https://doi.org/10.1007/978-1-349-14540-9 architectures for different vulnerability detection tasks by introducing neural network architecture search (NAS) techniques. Specifically, we design a more efficient search space to ensure superior neural network architectures can be found by the search algorithm. Besides, we propose an adaptive d作者: 感情脆弱 時間: 2025-3-29 21:54
Christian Morrisson,Béchir Talbiorporate policy descriptions as external knowledge into the model. Meanwhile, a GeoEncoder is designed which encourages the model to capture unobserved background factors specified by each region and then represent them as non-text information. We evaluate the performance of a broad range of baselin作者: 壓艙物 時間: 2025-3-30 02:34 作者: Apoptosis 時間: 2025-3-30 04:47
0302-9743 for Advanced Applications, DASFAA 2023, held in April 2023 in Tianjin, China..The total of 125 full papers, along with 66 short papers, are presented together in this four-volume set was carefully reviewed and selected from 652 submissions. Additionally, 15 industrial papers, 15 demo papers and 4 Ph作者: 組裝 時間: 2025-3-30 09:11 作者: Mundane 時間: 2025-3-30 15:37 作者: 職業(yè) 時間: 2025-3-30 18:04 作者: hemoglobin 時間: 2025-3-30 23:08 作者: 跑過 時間: 2025-3-31 04:15
Meta Pseudo Labels for?Anomaly Detection via?Partially Observed Anomaliesedback of a student network on a validation set, thereby generating more conducive pseudo anomalies to assist the student network while incurring less confirmation bias. Extensive experiments show that the proposed MPAD algorithm outperforms current popular algorithms on five real datasets.作者: Meander 時間: 2025-3-31 06:21 作者: macular-edema 時間: 2025-3-31 11:21
Restoration of Degraded Ecosystems well by outperforming other baselines in accuracy, response time, and memory footprint. Meanwhile, our method can scale to half a million data points on a personal computer, further verifying its cost-effectiveness.作者: 類似思想 時間: 2025-3-31 16:06
https://doi.org/10.1007/978-3-662-04072-0 samples while keeping the category information. We comprehensively verified the effectiveness of our model on both the normal and the semantic adhesion scenario of the few-shot open-set recognition problem.作者: Little 時間: 2025-3-31 21:06
Corporate Ethics and Management Theoryace. In addition, ST-LFC reduces the negative effects of unreliable predictions through entropy minimization. Empirical results indicate that ST-LFC significantly improves over the state-of-the-arts on a variety of benchmark datasets.作者: cutlery 時間: 2025-4-1 00:23 作者: 控訴 時間: 2025-4-1 03:14
