標(biāo)題: Titlebook: Database Systems for Advanced Applications; 27th International C Arnab Bhattacharya,Janice Lee Mong Li,Rage Uday Ki Conference proceedings [打印本頁(yè)] 作者: CURD 時(shí)間: 2025-3-21 18:59
書(shū)目名稱(chēng)Database Systems for Advanced Applications影響因子(影響力)
書(shū)目名稱(chēng)Database Systems for Advanced Applications影響因子(影響力)學(xué)科排名
書(shū)目名稱(chēng)Database Systems for Advanced Applications網(wǎng)絡(luò)公開(kāi)度
書(shū)目名稱(chēng)Database Systems for Advanced Applications網(wǎng)絡(luò)公開(kāi)度學(xué)科排名
書(shū)目名稱(chēng)Database Systems for Advanced Applications被引頻次
書(shū)目名稱(chēng)Database Systems for Advanced Applications被引頻次學(xué)科排名
書(shū)目名稱(chēng)Database Systems for Advanced Applications年度引用
書(shū)目名稱(chēng)Database Systems for Advanced Applications年度引用學(xué)科排名
書(shū)目名稱(chēng)Database Systems for Advanced Applications讀者反饋
書(shū)目名稱(chēng)Database Systems for Advanced Applications讀者反饋學(xué)科排名
作者: 進(jìn)步 時(shí)間: 2025-3-21 21:28 作者: Glutinous 時(shí)間: 2025-3-22 01:08
0302-9743 dvanced Applications, DASFAA 2022, held online, in April 2021...The total of 72 full papers, along with 76 short papers, are presented in this three-volume set was carefully reviewed and selected from 543 submissions. Additionally, 13 industrial papers, 9 demo papers and 2 PhD consortium papers are 作者: extrovert 時(shí)間: 2025-3-22 07:07 作者: 小蟲(chóng) 時(shí)間: 2025-3-22 12:27
https://doi.org/10.1007/978-3-319-50820-7emory and use GPU to accelerate the execution of AQP queries in addition to using GPU to accelerate the bootstrap-based error estimation. Extensive experiments on the SSB benchmark show that our GPU-accelerated method is at most about two orders of magnitude faster than the CPU method.作者: Arthropathy 時(shí)間: 2025-3-22 16:07 作者: Arthropathy 時(shí)間: 2025-3-22 17:56
https://doi.org/10.1007/978-981-10-3202-8ry. Furthermore, we restrict the RL action space of supernodes. Also, we use a dynamic reward instead of a binary reward in prior approaches. The experimental results on four benchmark datasets demonstrate that our approach significantly outperforms prior approaches.作者: 十字架 時(shí)間: 2025-3-22 22:57
Cross-Model Conjunctive Queries over Relation and Tree-Structured Dataal result of label values and encoded position values. Experimental results demonstrate the efficiency and scalability of the proposed techniques to answer a CMCQ in terms of running time and intermediate result size.作者: 切碎 時(shí)間: 2025-3-23 01:55
Revisiting Approximate Query Processing and Bootstrap Error Estimation on GPUemory and use GPU to accelerate the execution of AQP queries in addition to using GPU to accelerate the bootstrap-based error estimation. Extensive experiments on the SSB benchmark show that our GPU-accelerated method is at most about two orders of magnitude faster than the CPU method.作者: 生存環(huán)境 時(shí)間: 2025-3-23 08:12 作者: nonsensical 時(shí)間: 2025-3-23 10:02 作者: rheumatism 時(shí)間: 2025-3-23 17:26 作者: Apoptosis 時(shí)間: 2025-3-23 18:31 作者: 哀求 時(shí)間: 2025-3-24 00:49
Conference proceedings 2022was carefully reviewed and selected from 543 submissions. Additionally, 13 industrial papers, 9 demo papers and 2 PhD consortium papers are included...?..The conference was planned to take place in Hyderabad, India, but it was held virtually due to the COVID-19 pandemic. .作者: FIS 時(shí)間: 2025-3-24 04:56 作者: 修改 時(shí)間: 2025-3-24 09:34 作者: 有害處 時(shí)間: 2025-3-24 11:15
, Saturday , World Trade Center,ples from the query reachability graph without generating an excessive number of redundant intermediate results (a drawback of previous approaches). We experimentally verify the efficiency of our approach and demonstrate that it outperforms by far existing approaches and a recent graph DBMS on evalu作者: ALOFT 時(shí)間: 2025-3-24 18:44
Edward Sagarin,Donal E. J. Macnamarace via attention. Experiments demonstrate that FactE not only significantly outperforms state-of-the-art models but also brings remarkable benefits for disambiguation of 1-N relations, revealing its potential usefulness.作者: Fester 時(shí)間: 2025-3-24 21:19
https://doi.org/10.1007/978-981-10-3202-8e the ancestors of long-tailed relation classes into new relation representations to prevent the long-tailed relations from being ignored. Specifically, we use GraphSAGE to learn the relational knowledge from an existing knowledge graph via class embedding. Moreover, we aggregate the acquired relati作者: Nostalgia 時(shí)間: 2025-3-24 23:10 作者: Estimable 時(shí)間: 2025-3-25 03:53
Contemporary Medical Acupunctureard Expectation-Maximization to learn the best matching path iteratively. Extensive experiments on two popular KBQA datasets demonstrate the strong competitiveness of our model compared to previous state-of-the-art methods, especially in solving long path and spurious path problem.作者: Scintigraphy 時(shí)間: 2025-3-25 11:19
Reflex Arcs: Basis of Acupuncturebution to the query relation of each path and give each arrival path a different soft reward that can distinguish its validity. In addition, our method leverages the curiosity mechanism to generate curiosity-driven intrinsic rewards, which can not only alleviate the reward sparsity issue but also dr作者: 喪失 時(shí)間: 2025-3-25 12:52
Disorders of the Nervous System method to get a small set of instances for NVC. Based on the small training set, we modify the basic two-step positive-unlabeled learning strategy to train the model. Extensive evaluations demonstrate that our model significantly outperforms a variety of baseline approaches.作者: absorbed 時(shí)間: 2025-3-25 19:12 作者: Indent 時(shí)間: 2025-3-25 21:30
https://doi.org/10.1007/978-1-349-00332-7h can capture trajectory’s future moving goal, so as to provide long-term information for spatio-temporal joint prediction. Furthermore, we carefully design a gating mechanism to fuse sequential and intentional information with different weights to reflect their importance in capturing current movem作者: biopsy 時(shí)間: 2025-3-26 02:23 作者: Psa617 時(shí)間: 2025-3-26 06:41 作者: dowagers-hump 時(shí)間: 2025-3-26 12:11 作者: 宇宙你 時(shí)間: 2025-3-26 14:12 作者: antedate 時(shí)間: 2025-3-26 19:10
Triple-as-Node Knowledge Graph and?Its Embeddingsce via attention. Experiments demonstrate that FactE not only significantly outperforms state-of-the-art models but also brings remarkable benefits for disambiguation of 1-N relations, revealing its potential usefulness.作者: brassy 時(shí)間: 2025-3-26 21:39
LeKAN: Extracting Long-tail Relations via Layer-Enhanced Knowledge-Aggregation Networkse the ancestors of long-tailed relation classes into new relation representations to prevent the long-tailed relations from being ignored. Specifically, we use GraphSAGE to learn the relational knowledge from an existing knowledge graph via class embedding. Moreover, we aggregate the acquired relati作者: 有其法作用 時(shí)間: 2025-3-27 03:21
TRHyTE: Temporal Knowledge Graph Embedding Based on Temporal-Relational Hyperplanes relation space first, and then explicitly projects transformed entities and relations into temporal-relational hyperplanes to learn time-relation-aware embeddings. Moreover, Gate Recurrent Unit is leveraged to simulate TKG evolution so as to capture temporal dependency between adjacent hyperplanes.作者: Palpable 時(shí)間: 2025-3-27 06:58
Improving Core Path Reasoning for the Weakly Supervised Knowledge Base Question Answeringard Expectation-Maximization to learn the best matching path iteratively. Extensive experiments on two popular KBQA datasets demonstrate the strong competitiveness of our model compared to previous state-of-the-art methods, especially in solving long path and spurious path problem.作者: Lymphocyte 時(shí)間: 2025-3-27 13:19 作者: 千篇一律 時(shí)間: 2025-3-27 15:49 作者: 揮舞 時(shí)間: 2025-3-27 19:57 作者: Deadpan 時(shí)間: 2025-3-28 01:06 作者: Receive 時(shí)間: 2025-3-28 03:12
Approximate Continuous Top-K Queries over Memory Limitation-Based Streaming Datalides. Existing efforts include exact-based algorithms and approximate-based algorithms. Their common idea is maintaining a small subset of objects in the window. When the window slides, query results could be found from this set as much as possible. However, the space cost of all existing efforts i作者: 協(xié)定 時(shí)間: 2025-3-28 06:35 作者: Flinch 時(shí)間: 2025-3-28 11:10
Leveraging Search History for Improving Person-Job Fit However, existing studies mainly focus on the . scenario, while neglecting another important channel for linking positions with job seekers, . .. Intuitively, search history contains rich user behavior in job seeking, reflecting important evidence for job intention of users..In this paper, we prese作者: 圓錐體 時(shí)間: 2025-3-28 17:24
Efficient In-Memory Evaluation of Reachability Graph Pattern Queries on Data Graphsnalysis of large data graphs. In this paper, we present a novel approach for efficiently finding homomorphic matches of graph pattern queries, where pattern edges denote reachability relationships between nodes in the data graph. We first propose the concept of query reachability graph to compactly 作者: NEG 時(shí)間: 2025-3-28 22:39 作者: SKIFF 時(shí)間: 2025-3-29 01:20
-join: Efficient Join with Versioned Dimension Tablesces and contexts that are referenced from the fact tables. Analytical business queries join both tables to provide and verify business findings. Business resources and contexts are not necessarily constant; the dimension table may be updated at times. Versioning preserves every version of a dimensio作者: Type-1-Diabetes 時(shí)間: 2025-3-29 04:01 作者: Measured 時(shí)間: 2025-3-29 10:24
Triple-as-Node Knowledge Graph and?Its Embeddingsct triples (.). However, most previous KGs only consider the relationship between individual entities, ignoring connections between facts and entities, which are commonly used to depict useful information about the properties of facts. To this end, we formally introduce ., a new KG form which incorp作者: indignant 時(shí)間: 2025-3-29 14:22 作者: 剛開(kāi)始 時(shí)間: 2025-3-29 15:51
TRHyTE: Temporal Knowledge Graph Embedding Based on Temporal-Relational Hyperplanesyperplane-based TKGE approach, namely HyTE, has achieved remarkable performance, it still suffers from several problems including (i) ignorance of latent temporal properties and diversity of relations; (ii) neglect of temporal dependency between adjacent hyperplanes; (iii) inefficient static random 作者: mechanism 時(shí)間: 2025-3-29 21:04
ExKGR: Explainable Multi-hop Reasoning for?Evolving Knowledge Graphdding-based approach, multi-hop reasoning approach is more interpretable. Multi-hop reasoning can be modeled as . (RL) in which the RL agent navigates in the KG. Despite high interpretability, the knowledge in real world evolves by the minute, previous approaches are based on static KG. To address t作者: 撫慰 時(shí)間: 2025-3-30 02:05 作者: 加劇 時(shí)間: 2025-3-30 05:30
Counterfactual-Guided and Curiosity-Driven Multi-hop Reasoning over Knowledge Grapheffectiveness and interpretability. It typically adopts the Reinforcement Learning (RL) framework and traverses over the KG to reach the target answer and find evidential paths. However, existing methods often give all reached paths equal hit rewards. Intuitively, not all paths have the same contrib作者: 提名 時(shí)間: 2025-3-30 08:36 作者: 閃光你我 時(shí)間: 2025-3-30 15:53
JS-STDGN: A Spatial-Temporal Dynamic Graph Network Using JS-Graph for Traffic Prediction traffic management agencies. However, since road traffic is decided by multiple static and dynamic factors, traffic prediction is still a challenging task. As the core indicator of traffic condition, many works focus on traffic speed prediction using time-series forecasting approaches. Although cur作者: Saline 時(shí)間: 2025-3-30 20:14 作者: 青春期 時(shí)間: 2025-3-31 00:25 作者: Accessible 時(shí)間: 2025-3-31 02:25
978-3-031-00122-2The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl作者: obtuse 時(shí)間: 2025-3-31 05:28 作者: CHAR 時(shí)間: 2025-3-31 11:07 作者: confederacy 時(shí)間: 2025-3-31 13:55
https://doi.org/10.1007/978-3-319-50820-7olume of different types of data, there is little research to study the conjunctive queries between relation and tree data. In this paper, we study Cross-Model Conjunctive Queries (CMCQs) over relation and tree-structured data (XML and JSON). To efficiently process CMCQs with bounded intermediate re作者: Chronological 時(shí)間: 2025-3-31 18:55 作者: 技術(shù) 時(shí)間: 2025-4-1 01:00 作者: 轎車(chē) 時(shí)間: 2025-4-1 04:23
