標(biāo)題: Titlebook: Database Systems for Advanced Applications; 26th International C Christian S. Jensen,Ee-Peng Lim,Chih-Ya Shen Conference proceedings 2021 T [打印本頁] 作者: TEMPO 時(shí)間: 2025-3-21 17:44
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: AWE 時(shí)間: 2025-3-21 21:12
978-3-030-73193-9The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl作者: pessimism 時(shí)間: 2025-3-22 00:26
Lecture Notes in Computer Sciencehttp://image.papertrans.cn/d/image/263409.jpg作者: 小爭吵 時(shí)間: 2025-3-22 05:22
International Series on Consumer ScienceWe propose a data model for investigating constraints that enforce the entity integrity of semi-structured big data. Particular support is given for the volume, variety, and veracity dimensions of big data.作者: LUCY 時(shí)間: 2025-3-22 09:11 作者: 失望未來 時(shí)間: 2025-3-22 15:34 作者: 失望未來 時(shí)間: 2025-3-22 18:49
Lester D. Taylor,H.S. Houthakkeral whole, while the implicit semantic associations behind highly complex interactions of graphs are largely unexploited. In this paper, we propose a Semantic Graph Convolutional Networks (SGCN) that explores the implicit semantics by learning latent semantic-paths in graphs. In previous work, there 作者: uveitis 時(shí)間: 2025-3-22 21:58
Towards Consumer Demographic Perspectiveso the query and analysis of massive data. However, the insufficient utilization of system resources is an inherent problem of distributed computing engines. Particularly, when more jobs lead to execution blocking, the system schedules multiple jobs on a first-come-first-executed (FCFE) basis, even i作者: Alopecia-Areata 時(shí)間: 2025-3-23 02:30
Jo M. Martins,Farhat Yusuf,David A. Swansonshift, i.e. that the conditional distributions of data in different clients are disagreeing. A natural solution is to group clients with similar conditional distributions into the same cluster. However, methods following this approach leverage features extracted in federated settings (e.g., model we作者: giggle 時(shí)間: 2025-3-23 06:38 作者: prosperity 時(shí)間: 2025-3-23 10:54
https://doi.org/10.1007/978-1-4471-4640-7d servers. Although cloud computing brings significant advantages to data owners, the data stored in the cloud also faces many internal/external security attacks. Existing certificateless data provider schemes have the following two common shortcomings, i.e., most of which use plaintext to store dat作者: integrated 時(shí)間: 2025-3-23 14:05 作者: CHANT 時(shí)間: 2025-3-23 21:37
Bingbing Ni,Gang Wang,Pierre Moulinneering domains. Considering the characteristics of Big Data including quick generation, large size, and diverse data models, higher requirements are placed on the functionality and performance of database management systems. Therefore, it is essential for users to choose a stable and reliable datab作者: 發(fā)源 時(shí)間: 2025-3-24 01:22
Internet and Consumer Economic Wellbeingly proposed Hydra, a workload-aware and scale-free data regenerator that provides statistical fidelity on the volumetric similarity metric. A limitation, however, is that it suffers poor accuracy on unseen queries. In this paper, we present HF-Hydra (HiFi-Hydra), which extends Hydra to provide bette作者: Fierce 時(shí)間: 2025-3-24 06:19
https://doi.org/10.1007/978-3-030-14564-4ost widely used supervision component is an output layer together with classification loss (e.g., cross-entropy loss together with softmax or margin loss). In fact, the discriminative information among instances are more fine-grained, which can benefit graph classification tasks. In this paper, we p作者: onlooker 時(shí)間: 2025-3-24 08:39
Jan Logemann,Gary Cross,Ingo K?hleror disconnected) of node pair can not be observed. If we can get more useful information hidden in node pairs with unknown link status, it will help improve the performance of network embedding. Therefore, how to model the network with unknown link status actively and effectively remains an area for作者: 發(fā)怨言 時(shí)間: 2025-3-24 13:16
Consumer Engineering, 1920s–1970s works. However, existing community search studies over heterogeneous information networks ignore the importance of keywords and cannot be directly applied to the keyword-centric community search problem. To deal with these problems, we propose .-core, which is defined based on a densely-connected s作者: Retrieval 時(shí)間: 2025-3-24 17:39 作者: STYX 時(shí)間: 2025-3-24 19:35 作者: Infiltrate 時(shí)間: 2025-3-25 01:08 作者: 不可比擬 時(shí)間: 2025-3-25 05:11 作者: 漂泊 時(shí)間: 2025-3-25 09:16
Partial Solutions for Patient Safetyletion methods are known to be primarily knowledge embedding based models, which are broadly classified as translational models and neural network models. However, both kinds of models are single-task based models and hence fail to capture the underlying inter-structural relationships that are inher作者: phytochemicals 時(shí)間: 2025-3-25 12:47
Multi-job Merging Framework and Scheduling Optimization for Apache Flinkighlighted as follows: (1) the framework enables Flink to support multi-job collection, merging and dynamic tuning of the execution sequence, and the selection of these functions are customizable. (2) with the multi-job merging and optimization, the total running time can be reduced by 31% compared 作者: stress-response 時(shí)間: 2025-3-25 19:07 作者: 花費(fèi) 時(shí)間: 2025-3-25 19:58
vRaft: Accelerating the Distributed Consensus Under Virtualized Environments followers to accelerate both the write and the read requests processing in a virtualized cloud environment, without affecting the linearizability guarantee of Raft. The experiments based on the virtual nodes in Tencent Cloud indicate that vRaft improves the throughput by up?to 64.2%, reduces averag作者: Inscrutable 時(shí)間: 2025-3-26 03:45 作者: 背信 時(shí)間: 2025-3-26 07:18
Label Contrastive Coding Based Graph Neural Network for Graph Classificationc label memory bank and a momentum updated encoder. Our extensive evaluations with eight benchmark graph datasets demonstrate that LCGNN can outperform state-of-the-art graph classification models. Experimental results also verify that LCGNN can achieve competitive performance with less training dat作者: 共棲 時(shí)間: 2025-3-26 11:57
Keyword-Centric Community Search over Large Heterogeneous Information Networks design an advanced algorithm .-core using a new method of traversing the search space based on trees to accelerate the searching procedure. For online queries, we optimize the approach with a new index to handle the online queries of community search over HINs. Extensive experiments on HINs are con作者: 和平主義 時(shí)間: 2025-3-26 15:01
KGSynNet: A Novel Entity Synonyms Discovery Framework with Knowledge Graphedge information into their semantic features. We conduct extensive experiments to demonstrate the effectiveness of our . in leveraging the knowledge graph. The experimental results show that the . improves the state-of-the-art methods by 14.7% in terms of hits@3 in the offline evaluation and outper作者: 虛假 時(shí)間: 2025-3-26 18:17 作者: Fibroid 時(shí)間: 2025-3-26 23:56
Spatial-Temporal Attention Network for Temporal Knowledge Graph Completiontructural information from the egocentric network of each entity. Additionally, an .aptive .emporal .tention Mechanism (ADTAT) is utilized to flexibly model the correlation of entity representations in the time dimension. Finally, by combing our obtained representations with existing static KG compl作者: CHIDE 時(shí)間: 2025-3-27 04:02 作者: cringe 時(shí)間: 2025-3-27 08:51
A Novel Embedding Model for Knowledge Graph Completion Based on Multi-Task Learningn the global representation of each triple element. Such global representations are then integrated into task-specific translational embedding models of each knowledge graph to preserve its transition property. We conduct an extensive empirical evaluation of multi-version . based on different transl作者: Progesterone 時(shí)間: 2025-3-27 10:46 作者: 擺動 時(shí)間: 2025-3-27 14:43 作者: Landlocked 時(shí)間: 2025-3-27 21:14 作者: 享樂主義者 時(shí)間: 2025-3-27 22:26
https://doi.org/10.1007/978-1-4471-4640-7the third-party verifier can audit the integrity of ciphertext without downloading the whole encrypted data. Security analysis shows that our proposed scheme is provably secure under the random oracle model. An evaluation of performance shows that our proposed scheme is efficient in terms of computa作者: LAST 時(shí)間: 2025-3-28 03:09 作者: 蕨類 時(shí)間: 2025-3-28 10:05
Consumer Engineering, 1920s–1970s design an advanced algorithm .-core using a new method of traversing the search space based on trees to accelerate the searching procedure. For online queries, we optimize the approach with a new index to handle the online queries of community search over HINs. Extensive experiments on HINs are con作者: wall-stress 時(shí)間: 2025-3-28 10:48
https://doi.org/10.1007/978-3-030-14564-4edge information into their semantic features. We conduct extensive experiments to demonstrate the effectiveness of our . in leveraging the knowledge graph. The experimental results show that the . improves the state-of-the-art methods by 14.7% in terms of hits@3 in the offline evaluation and outper作者: 廢除 時(shí)間: 2025-3-28 17:31 作者: HEAVY 時(shí)間: 2025-3-28 20:44
Tanusree Dutta,Manas Kumar Mandaltructural information from the egocentric network of each entity. Additionally, an .aptive .emporal .tention Mechanism (ADTAT) is utilized to flexibly model the correlation of entity representations in the time dimension. Finally, by combing our obtained representations with existing static KG compl作者: blackout 時(shí)間: 2025-3-28 23:01
Partial Solutions for Patient Safetyl space and consequently fulfill entity ranking on the embedding. Finally, we conduct an extensive experimental study on real-life datasets, and verify the effectiveness of our proposed approach compared to competitive baselines.作者: Barter 時(shí)間: 2025-3-29 06:19 作者: 友好 時(shí)間: 2025-3-29 08:04 作者: Malcontent 時(shí)間: 2025-3-29 11:23
Internet and Consumer Economic Wellbeingr support to unseen queries through (a) careful choices among the candidate synthetic databases and (b) incorporation of metadata constraints. Our experimental study validates the improved fidelity and efficiency of HF-Hydra.作者: 有幫助 時(shí)間: 2025-3-29 17:10 作者: 輕率看法 時(shí)間: 2025-3-29 21:00 作者: 外形 時(shí)間: 2025-3-30 00:17 作者: jovial 時(shí)間: 2025-3-30 07:54 作者: RECUR 時(shí)間: 2025-3-30 11:29 作者: SOW 時(shí)間: 2025-3-30 14:00
0302-9743 network, recommendation, graph, learning, and model. These topic areas and keywords shed the light on the direction where the research in DASFAA is moving towards...Due to the Corona pandemic this event was held virtually..978-3-030-73193-9978-3-030-73194-6Series ISSN 0302-9743 Series E-ISSN 1611-3349 作者: 自作多情 時(shí)間: 2025-3-30 17:23 作者: Subjugate 時(shí)間: 2025-3-30 23:56 作者: archetype 時(shí)間: 2025-3-31 02:13 作者: BARGE 時(shí)間: 2025-3-31 08:22 作者: 作繭自縛 時(shí)間: 2025-3-31 12:33
UniTest: A Universal Testing Framework for Database Management Systemsuniversal testing framework, called UniTest, which can perform effective functional testing and performance testing for different types of database management systems. Extensive testing experiments on multiple types of database management systems show the universality and efficiency of our framework.作者: 易于交談 時(shí)間: 2025-3-31 15:58 作者: 新奇 時(shí)間: 2025-3-31 17:41
Learning the Implicit Semantic Representation on Graph-Structured Dataal whole, while the implicit semantic associations behind highly complex interactions of graphs are largely unexploited. In this paper, we propose a Semantic Graph Convolutional Networks (SGCN) that explores the implicit semantics by learning latent semantic-paths in graphs. In previous work, there 作者: 獨(dú)行者 時(shí)間: 2025-4-1 01:31 作者: 挑剔為人 時(shí)間: 2025-4-1 04:29 作者: Perigee 時(shí)間: 2025-4-1 08:47 作者: 事與愿違 時(shí)間: 2025-4-1 12:19
