Advances in database technology : proceedings. International Conference on Extending Database Technology最新文献_第3页

Recommending Unanimously Preferred Items to Groups 向组推荐一致首选项目

Advances in database technology : proceedings. International Conference on Extending Database Technology Pub Date : 2023-01-01 DOI: 10.48786/edbt.2023.29

Karim Benouaret, K. Tan

引用次数: 0

Data Narration for the People: Challenges and Opportunities 面向人民的数据叙事:挑战与机遇

Advances in database technology : proceedings. International Conference on Extending Database Technology Pub Date : 2023-01-01 DOI: 10.48786/edbt.2023.82

S. Amer-Yahia, Patrick Marcel, Verónika Peralta

引用次数: 0

Multi-Dimensional Data Publishing With Local Differential Privacy 具有局部差分隐私的多维数据发布

Advances in database technology : proceedings. International Conference on Extending Database Technology Pub Date : 2023-01-01 DOI: 10.48786/edbt.2023.15

Gaoyuan Liu, Peng Tang, Chengyu Hu, Chongshi Jin, Shanqing Guo

{"title":"Multi-Dimensional Data Publishing With Local Differential Privacy","authors":"Gaoyuan Liu, Peng Tang, Chengyu Hu, Chongshi Jin, Shanqing Guo","doi":"10.48786/edbt.2023.15","DOIUrl":"https://doi.org/10.48786/edbt.2023.15","url":null,"abstract":"This paper studies the publication of multi-dimensional data with local differential privacy (LDP). This problem raises tremendous challenges in terms of both computational efficiency and data utility. The state-of-the-art solution addresses this problem by first constructing a junction tree (a kind of probabilistic graphical model, PGM) to generate a set of noisy low-dimensional marginals of the input data and then using them to approximate the distribution of the input dataset for synthetic data generation. However, there are two severe limitations in the existing solution, i.e., calculating a large number of attribute pairs’ marginals to construct the PGM and not solving well in calculating the marginal distribution of large cliques in the PGM, which degrade the quality of synthetic data. To address the above deficiencies, based on the sparseness of the constructed PGM and the divisibility of LDP, we first propose an incremental learning-based PGM construction method. In this method, we gradually prune the edges (attribute pairs) with weak correlation and allocate more data and privacy budgets to the useful edges, thereby improving the model’s accuracy. In this method, we introduce a high-precision data accumulation technique and a low-error edge pruning technique. Second, based on joint distribution decomposition and redundancy elimination, we propose a novel marginal calculation method for the large cliques in the context of LDP. Extensive experiments on real datasets demonstrate that our solution offers desirable data utility.","PeriodicalId":88813,"journal":{"name":"Advances in database technology : proceedings. International Conference on Extending Database Technology","volume":"18 1","pages":"183-194"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86073013","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 6

Joint Source and Schema Evolution: Insights from a Study of 195 FOSS Projects 联合源和模式演化:来自195个自由/开源软件项目研究的见解

Advances in database technology : proceedings. International Conference on Extending Database Technology Pub Date : 2023-01-01 DOI: 10.48786/edbt.2023.03

Panos Vassiliadis, Fation Shehaj, George Kalampokis, A. Zarras

{"title":"Joint Source and Schema Evolution: Insights from a Study of 195 FOSS Projects","authors":"Panos Vassiliadis, Fation Shehaj, George Kalampokis, A. Zarras","doi":"10.48786/edbt.2023.03","DOIUrl":"https://doi.org/10.48786/edbt.2023.03","url":null,"abstract":"In this paper, we address the problem of the co-evolution of Free Open Source Software projects with the relational schemata that they encompass. We exploit a data set of 195 publicly available schema histories of FOSS projects hosted in Github, for which we locally cloned their respective project and measured their evolution progress. Our first research question asks which percentage of the projects demonstrates a “hand-in-hand” schema and source code co-evolution? To address this question, we defined synchronicity by allowing a bounded amount of lag between the cumulative evolution of the schema and the entire project. A core finding is that there are all kinds of behaviors with respect to project and schema co-evolution, resulting in only a small number of projects where the evolution of schema and project progress in sync. Moreover, we discovered that after exceeding a 5-year threshold of project life, schemata gravitate to lower rates of evolution, which practically means that, with time, the schemata stop evolving as actively as they originally did. To answer a second question, on whether evolution comes early in the life of a schema, we measured how often does the cumulative progress of schema evolution exceed the respective progress of source change, as well as the respective progress of time. The results indicate that a large majority of schemata demonstrates early advance of schema change with respect to code evolution, and, an even larger majority is also demonstrating an advance of schema evolution with respect to time, too. Third, we asked at which time point in their lives do schemata attain a substantial","PeriodicalId":88813,"journal":{"name":"Advances in database technology : proceedings. International Conference on Extending Database Technology","volume":"4 1","pages":"27-39"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90532072","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Data Provenance for SHACL 用于acl的数据来源

Advances in database technology : proceedings. International Conference on Extending Database Technology Pub Date : 2023-01-01 DOI: 10.48786/edbt.2023.23

Thomas Delva, Maxim Jakubowski

引用次数: 0

Stitcher: Learned Workload Synthesis from Historical Performance Footprints 缝制工:从历史性能足迹中学习工作量合成

Advances in database technology : proceedings. International Conference on Extending Database Technology Pub Date : 2023-01-01 DOI: 10.48786/edbt.2023.33

Chengcheng Wan, Yiwen Zhu, Joyce Cahoon, Wenjing Wang, K. Lin, Sean Liu, Raymond Truong, Neetu Singh, Alexandra Ciortea, Konstantinos Karanasos, Subru Krishnan

{"title":"Stitcher: Learned Workload Synthesis from Historical Performance Footprints","authors":"Chengcheng Wan, Yiwen Zhu, Joyce Cahoon, Wenjing Wang, K. Lin, Sean Liu, Raymond Truong, Neetu Singh, Alexandra Ciortea, Konstantinos Karanasos, Subru Krishnan","doi":"10.48786/edbt.2023.33","DOIUrl":"https://doi.org/10.48786/edbt.2023.33","url":null,"abstract":"Database benchmarking and workload replay have been widely used to drive system design, evaluate workload performance, de-termine product evolution, and guide cloud migration. However, they both suffer from some key limitations: the former fails to capture the variety and complexity of production workloads; the latter requires access to user data, queries, and machine specifications, deeming it inapplicable in the face of user privacy concerns. Here we introduce our vision of learned workload synthesis to overcome these issues: given the performance profile of a customer workload (e.g., CPU/memory counters), synthesize a new workload that yields the same performance profile when executed on a range of hardware/software configurations. We present Stitcher as a first step towards realizing this vision, which synthesizes workloads by combining pieces from standard benchmarks. We believe that our vision will spark new research avenues in database workload replay.","PeriodicalId":88813,"journal":{"name":"Advances in database technology : proceedings. International Conference on Extending Database Technology","volume":"108 1","pages":"417-423"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91107488","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Understanding crowd energy consumption behaviors 了解人群能源消耗行为

Advances in database technology : proceedings. International Conference on Extending Database Technology Pub Date : 2023-01-01 DOI: 10.48786/edbt.2023.68

X. Liu, Xu Cheng, Yanyan Yang, Huan Huo, Yongping Liu, P. S. Nielsen

引用次数: 0

Pushing Edge Computing one Step Further: Resilient and Privacy-Preserving Processing on Personal Devices 进一步推动边缘计算:个人设备上的弹性和隐私保护处理

Advances in database technology : proceedings. International Conference on Extending Database Technology Pub Date : 2023-01-01 DOI: 10.48786/edbt.2023.77

Ludovic Javet, N. Anciaux, Luc Bouganim, Léo Lamoureux, P. Pucheral

引用次数: 0

REQUIRED: A Tool to Relax Queries through Relaxed Functional Dependencies 需要:一个通过放松的功能依赖来放松查询的工具

Advances in database technology : proceedings. International Conference on Extending Database Technology Pub Date : 2023-01-01 DOI: 10.48786/edbt.2023.74

Loredana Caruccio, Stefano Cirillo, V. Deufemia, G. Polese, R. Stanzione

引用次数: 0

Efficient Multi-Model Management 高效的多模式管理

Advances in database technology : proceedings. International Conference on Extending Database Technology Pub Date : 2023-01-01 DOI: 10.48786/edbt.2023.37

Nils Strassenburg, Dominic Kupfer, J. Kowal, T. Rabl

{"title":"Efficient Multi-Model Management","authors":"Nils Strassenburg, Dominic Kupfer, J. Kowal, T. Rabl","doi":"10.48786/edbt.2023.37","DOIUrl":"https://doi.org/10.48786/edbt.2023.37","url":null,"abstract":"Deep learning models are deployed in an increasing number of industrial domains, such as retail and automotive applications. An instance of a model typically performs one specific task, which is why larger software systems use multiple models in parallel. Given that all models in production software have to be managed, this leads to the problem of managing sets of related models, i.e., multi-model management. Existing approaches perform poorly on this task because they are optimized for saving single large models but not for simultaneously saving a set of related models. In this paper, we explore the space of multi-model management by presenting three optimized approaches: (1) A baseline approach that saves full model representations and minimizes the amount of saved metadata. (2) An update approach that reduces the storage consumption compared to the baseline by saving parameter updates instead of full models. (3) A provenance approach that saves model provenance data instead of model parameters. We evaluate the approaches for the multi-model management use cases of managing car battery cell models and image classification models. Our results show that the baseline outperforms existing approaches for save and recover times by more than an order of magnitude and that more sophisticated approaches reduce the storage consumption by up to 99%.","PeriodicalId":88813,"journal":{"name":"Advances in database technology : proceedings. International Conference on Extending Database Technology","volume":"77 1","pages":"457-463"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86764458","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1