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Distributed and Parallel Databases最新文献

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A spatial co-location pattern mining framework insensitive to prevalence thresholds based on overlapping cliques 一种基于重叠集团的对流行阈值不敏感的空间协同定位模式挖掘框架
IF 1.2 4区 计算机科学 Q3 Decision Sciences Pub Date : 2021-03-18 DOI: 10.1007/s10619-021-07333-2
Vanha Tran, Lizhen Wang, Lihua Zhou
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引用次数: 6
Finding the most profitable candidate product by dynamic skyline and parallel processing 采用动态天际线并行处理的方法寻找最具盈利能力的候选产品
IF 1.2 4区 计算机科学 Q3 Decision Sciences Pub Date : 2021-03-18 DOI: 10.1007/s10619-021-07323-4
Liang Kuang Tai, En Tzu Wang, Arbee L. P. Chen
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引用次数: 2
On the necessity of explicit cross-layer data formats in near-data processing systems 近数据处理系统中显式跨层数据格式的必要性
IF 1.2 4区 计算机科学 Q3 Decision Sciences Pub Date : 2021-03-16 DOI: 10.1007/s10619-021-07328-z
Lukas Weber, Tobias Vinçon, Christian Knödler, Leonardo Solis-Vasquez, Arthur Bernhardt, Ilia Petrov, Andreas Koch
{"title":"On the necessity of explicit cross-layer data formats in near-data processing systems","authors":"Lukas Weber, Tobias Vinçon, Christian Knödler, Leonardo Solis-Vasquez, Arthur Bernhardt, Ilia Petrov, Andreas Koch","doi":"10.1007/s10619-021-07328-z","DOIUrl":"https://doi.org/10.1007/s10619-021-07328-z","url":null,"abstract":"","PeriodicalId":50568,"journal":{"name":"Distributed and Parallel Databases","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2021-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1007/s10619-021-07328-z","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41479725","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A hybrid machine learning approach to identify coronary diseases using feature selection mechanism on heart disease dataset 基于特征选择机制的混合机器学习方法在心脏病数据集上识别冠心病
IF 1.2 4区 计算机科学 Q3 Decision Sciences Pub Date : 2021-03-15 DOI: 10.1007/s10619-021-07329-y
Bhanu Prakash Doppala, D. Bhattacharyya, Midhun Chakkravarthy, Tai-hoon Kim
{"title":"A hybrid machine learning approach to identify coronary diseases using feature selection mechanism on heart disease dataset","authors":"Bhanu Prakash Doppala, D. Bhattacharyya, Midhun Chakkravarthy, Tai-hoon Kim","doi":"10.1007/s10619-021-07329-y","DOIUrl":"https://doi.org/10.1007/s10619-021-07329-y","url":null,"abstract":"","PeriodicalId":50568,"journal":{"name":"Distributed and Parallel Databases","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2021-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1007/s10619-021-07329-y","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42700807","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 10
An enhanced visual approach for accessing the clustering tendency of big data 一种访问大数据聚类趋势的增强可视化方法
IF 1.2 4区 计算机科学 Q3 Decision Sciences Pub Date : 2021-03-15 DOI: 10.1007/s10619-021-07330-5
Veluru Chinnaiah, B. Yadav
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引用次数: 0
Selective caching: a persistent memory approach for multi-dimensional index structures 选择性缓存:用于多维索引结构的持久内存方法
IF 1.2 4区 计算机科学 Q3 Decision Sciences Pub Date : 2021-03-14 DOI: 10.1007/s10619-021-07327-0
M. Jibril, Philipp Götze, David Broneske, K. Sattler
{"title":"Selective caching: a persistent memory approach for multi-dimensional index structures","authors":"M. Jibril, Philipp Götze, David Broneske, K. Sattler","doi":"10.1007/s10619-021-07327-0","DOIUrl":"https://doi.org/10.1007/s10619-021-07327-0","url":null,"abstract":"","PeriodicalId":50568,"journal":{"name":"Distributed and Parallel Databases","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2021-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1007/s10619-021-07327-0","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47953113","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Parallel query processing in a polystore 多存储库中的并行查询处理
IF 1.2 4区 计算机科学 Q3 Decision Sciences Pub Date : 2021-02-03 DOI: 10.1007/s10619-021-07322-5
Pavlos Kranas, B. Kolev, O. Levchenko, Esther Pacitti, P. Valduriez, R. Jiménez-Peris, M. Patiño-Martínez
{"title":"Parallel query processing in a polystore","authors":"Pavlos Kranas, B. Kolev, O. Levchenko, Esther Pacitti, P. Valduriez, R. Jiménez-Peris, M. Patiño-Martínez","doi":"10.1007/s10619-021-07322-5","DOIUrl":"https://doi.org/10.1007/s10619-021-07322-5","url":null,"abstract":"","PeriodicalId":50568,"journal":{"name":"Distributed and Parallel Databases","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2021-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1007/s10619-021-07322-5","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44103879","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 6
Semantic-based Big Data integration framework using scalable distributed ontology matching strategy 基于语义的大数据集成框架,采用可扩展的分布式本体匹配策略
IF 1.2 4区 计算机科学 Q3 Decision Sciences Pub Date : 2021-01-29 DOI: 10.1007/s10619-021-07321-6
Imadeddine Mountasser, B. Ouhbi, Ferdaous Hdioud, B. Frikh
{"title":"Semantic-based Big Data integration framework using scalable distributed ontology matching strategy","authors":"Imadeddine Mountasser, B. Ouhbi, Ferdaous Hdioud, B. Frikh","doi":"10.1007/s10619-021-07321-6","DOIUrl":"https://doi.org/10.1007/s10619-021-07321-6","url":null,"abstract":"","PeriodicalId":50568,"journal":{"name":"Distributed and Parallel Databases","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2021-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1007/s10619-021-07321-6","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44119382","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 11
Sensitive attribute privacy preservation of trajectory data publishing based on l-diversity. 基于l-多样性的轨迹数据发布敏感属性隐私保护。
IF 1.2 4区 计算机科学 Q3 Decision Sciences Pub Date : 2021-01-01 Epub Date: 2020-11-17 DOI: 10.1007/s10619-020-07318-7
Lin Yao, Zhenyu Chen, Haibo Hu, Guowei Wu, Bin Wu

The widely application of positioning technology has made collecting the movement of people feasible for knowledge-based decision. Data in its original form often contain sensitive attributes and publishing such data will leak individuals' privacy. Especially, a privacy threat occurs when an attacker can link a record to a specific individual based on some known partial information. Therefore, maintaining privacy in the published data is a critical problem. To prevent record linkage, attribute linkage, and similarity attacks based on the background knowledge of trajectory data, we propose a data privacy preservation with enhanced l-diversity. First, we determine those critical spatial-temporal sequences which are more likely to cause privacy leakage. Then, we perturb these sequences by adding or deleting some spatial-temporal points while ensuring the published data satisfy our ( L , α , β )-privacy, an enhanced privacy model from l-diversity. Our experiments on both synthetic and real-life datasets suggest that our proposed scheme can achieve better privacy while still ensuring high utility, compared with existing privacy preservation schemes on trajectory.

定位技术的广泛应用,为基于知识的决策提供了可能。原始形式的数据通常包含敏感属性,发布此类数据将泄露个人隐私。特别是,当攻击者可以根据某些已知的部分信息将记录链接到特定的个人时,就会发生隐私威胁。因此,维护发布数据的隐私性是一个关键问题。为了防止记录链接、属性链接和基于轨迹数据背景知识的相似性攻击,我们提出了一种增强l-多样性的数据隐私保护方法。首先,我们确定了那些更容易导致隐私泄露的关键时空序列。然后,我们通过增加或删除一些时空点来扰动这些序列,同时确保发布的数据满足我们的(L, α, β)隐私模型,这是一种来自L -多样性的增强隐私模型。我们在合成数据集和真实数据集上的实验表明,与现有的轨迹隐私保护方案相比,我们提出的方案可以在保证高效用的同时实现更好的隐私保护。
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引用次数: 9
A simplified variant of tabled asymmetric numeral systems with a smaller look-up table 具有较小查找表的表列非对称数字系统的简化变体
IF 1.2 4区 计算机科学 Q3 Decision Sciences Pub Date : 2020-10-30 DOI: 10.1007/s10619-020-07316-9
Na Wang, Chao Wang, Sian-Jheng Lin
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引用次数: 4
期刊
Distributed and Parallel Databases
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