Scientific and statistical database management : International Conference, SSDBM ... : proceedings. International Conference on Scientific and Statistical Database Management最新文献

Towards Co-Evolution of Data-Centric Ecosystems. 迈向以数据为中心的生态系统的共同进化。

Scientific and statistical database management : International Conference, SSDBM ... : proceedings. International Conference on Scientific and Statistical Database Management Pub Date : 2020-07-01 DOI: 10.1145/3400903.3400908

Robert Schuler, Karl Czajkowski, Mike D'Arcy, Hongsuda Tangmunarunkit, Carl Kesselman

引用次数: 8

Efficient classification of billions of points into complex geographic regions using hierarchical triangular mesh 利用分层三角网格对复杂地理区域的数十亿点进行高效分类

Scientific and statistical database management : International Conference, SSDBM ... : proceedings. International Conference on Scientific and Statistical Database Management Pub Date : 2014-06-30 DOI: 10.1145/2618243.2618245

Dániel Kondor, L. Dobos, I. Csabai, A. Bodor, G. Vattay, T. Budavári, A. Szalay

引用次数: 9

SensorBench: benchmarking approaches to processing wireless sensor network data SensorBench:处理无线传感器网络数据的基准测试方法

Scientific and statistical database management : International Conference, SSDBM ... : proceedings. International Conference on Scientific and Statistical Database Management Pub Date : 2014-06-30 DOI: 10.1145/2618243.2618252

I. Galpin, A. B. Stokes, G. Valkanas, A. Gray, N. Paton, A. Fernandes, K. Sattler, D. Gunopulos

{"title":"SensorBench: benchmarking approaches to processing wireless sensor network data","authors":"I. Galpin, A. B. Stokes, G. Valkanas, A. Gray, N. Paton, A. Fernandes, K. Sattler, D. Gunopulos","doi":"10.1145/2618243.2618252","DOIUrl":"https://doi.org/10.1145/2618243.2618252","url":null,"abstract":"Wireless sensor networks enable cost-effective data collection for tasks such as precision agriculture and environment monitoring. However, the resource-constrained nature of sensor nodes, which often have both limited computational capabilities and battery lifetimes, means that applications that use them must make judicious use of these resources. Research that seeks to support data intensive sensor applications has explored a range of approaches and developed many different techniques, including bespoke algorithms for specific analyses and generic sensor network query processors. However, all such proposals sit within a multi-dimensional design space, where it can be difficult to understand the implications of specific decisions and to identify optimal solutions. This paper presents a benchmark that seeks to support the systematic analysis and comparison of different techniques and platforms, enabling both development and user communities to make well informed choices. The contributions of the paper include: (i) the identification of key variables and performance metrics; (ii) the specification of experiments that explore how different types of task perform under different metrics for the controlled variables; and (iii) an application of the benchmark to investigate the behavior of several representative platforms and techniques.","PeriodicalId":74773,"journal":{"name":"Scientific and statistical database management : International Conference, SSDBM ... : proceedings. International Conference on Scientific and Statistical Database Management","volume":"31 1","pages":"21:1-21:12"},"PeriodicalIF":0.0,"publicationDate":"2014-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73367384","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

MR-microT: a MapReduce-based MicroRNA target prediction method MR-microT:一种基于mapreduce的MicroRNA靶标预测方法

Scientific and statistical database management : International Conference, SSDBM ... : proceedings. International Conference on Scientific and Statistical Database Management Pub Date : 2014-06-30 DOI: 10.1145/2618243.2618289

Ilias Kanellos, Thanasis Vergoulis, Dimitris Sacharidis, Theodore Dalamagas, A. Hatzigeorgiou, S. Sartzetakis, T. Sellis

引用次数: 18

(k, d)-core anonymity: structural anonymization of massive networks (k, d)-核心匿名:大规模网络的结构性匿名化

Scientific and statistical database management : International Conference, SSDBM ... : proceedings. International Conference on Scientific and Statistical Database Management Pub Date : 2014-06-30 DOI: 10.1145/2618243.2618269

Roland Assam, Marwan Hassani, M. Brysch, T. Seidl

{"title":"(k, d)-core anonymity: structural anonymization of massive networks","authors":"Roland Assam, Marwan Hassani, M. Brysch, T. Seidl","doi":"10.1145/2618243.2618269","DOIUrl":"https://doi.org/10.1145/2618243.2618269","url":null,"abstract":"Networks entail vulnerable and sensitive information that pose serious privacy threats. In this paper, we introduce, k-core attack, a new attack model which stems from the k-core decomposition principle. K-core attack undermines the privacy of some state-of-the-art techniques. We propose a novel structural anonymization technique called (k, Δ)-Core Anonymity, which harnesses the k-core attack and structurally anonymizes small and large networks. In addition, although real-world social networks are massive in nature, most existing works focus on the anonymization of networks with less than one hundred thousand nodes. (k, Δ)-Core Anonymity is tailored for massive networks. To the best of our knowledge, this is the first technique that provides empirical studies on structural network anonymization for massive networks. Using three real and two synthetic datasets, we demonstrate the effectiveness of our technique on small and large networks with up to 1.7 million nodes and 17.8 million edges. Our experiments reveal that our approach outperforms a state-of-the-art work in several aspects.","PeriodicalId":74773,"journal":{"name":"Scientific and statistical database management : International Conference, SSDBM ... : proceedings. International Conference on Scientific and Statistical Database Management","volume":"6 1","pages":"17:1-17:12"},"PeriodicalIF":0.0,"publicationDate":"2014-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87360927","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: 16

Efficient processing of exploratory top-k joins 有效处理探索性top-k连接

Scientific and statistical database management : International Conference, SSDBM ... : proceedings. International Conference on Scientific and Statistical Database Management Pub Date : 2014-06-30 DOI: 10.1145/2618243.2618280

Orestis Gkorgkas, Akrivi Vlachou, C. Doulkeridis, K. Nørvåg

{"title":"Efficient processing of exploratory top-k joins","authors":"Orestis Gkorgkas, Akrivi Vlachou, C. Doulkeridis, K. Nørvåg","doi":"10.1145/2618243.2618280","DOIUrl":"https://doi.org/10.1145/2618243.2618280","url":null,"abstract":"In this paper, we address the problem of discovering a ranked set of k distinct main objects combined with additional (accessory) objects that best fit the given preferences. This problem is challenging because it considers object combinations of variable size, where objects are combined only if the combination produces a higher score, and thus becomes more preferable to a user. In this way, users can explore overviews of combinations that are more suited to their preferences than single objects, without the need to explicitly specify which objects should be combined. We model this problem as a rank-join problem where each combination is represented by a set of tuples from different relations and we call the respective query eXploratory Top-k Join query. Existing approaches fall short to tackle this problem because they impose a fixed size of combinations, they do not distinguish on combinations based on the main objects or they do not take into account user preferences. We introduce a more efficient bounding scheme that can be used on an adaptation of the rank-join algorithm, which exploits some key properties of our problem and allows earlier termination of query processing. Our experimental evaluation demonstrates the efficiency of the proposed bounding technique.","PeriodicalId":74773,"journal":{"name":"Scientific and statistical database management : International Conference, SSDBM ... : proceedings. International Conference on Scientific and Statistical Database Management","volume":"30 1","pages":"35:1-35:4"},"PeriodicalIF":0.0,"publicationDate":"2014-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75193587","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: 2

Integrating fault-tolerance and elasticity in a distributed data stream processing system 在分布式数据流处理系统中集成容错和弹性

Scientific and statistical database management : International Conference, SSDBM ... : proceedings. International Conference on Scientific and Statistical Database Management Pub Date : 2014-06-30 DOI: 10.1145/2618243.2618288

Kasper Grud Skat Madsen, Philip Thyssen, Yongluan Zhou

引用次数: 18

Data patterns to alleviate the design of scientific workflows exemplified by a bone simulation 数据模式减轻科学工作流程的设计，以骨模拟为例

Scientific and statistical database management : International Conference, SSDBM ... : proceedings. International Conference on Scientific and Statistical Database Management Pub Date : 2014-06-30 DOI: 10.1145/2618243.2618279

P. Reimann, H. Schwarz, B. Mitschang

引用次数: 7

Skew-resistant parallel in-memory spatial join 抗歪斜并行内存空间连接

Scientific and statistical database management : International Conference, SSDBM ... : proceedings. International Conference on Scientific and Statistical Database Management Pub Date : 2014-06-30 DOI: 10.1145/2618243.2618262

S. Ray, Bogdan Simion, Angela Demke Brown, Ryan Johnson

{"title":"Skew-resistant parallel in-memory spatial join","authors":"S. Ray, Bogdan Simion, Angela Demke Brown, Ryan Johnson","doi":"10.1145/2618243.2618262","DOIUrl":"https://doi.org/10.1145/2618243.2618262","url":null,"abstract":"Spatial join is a crucial operation in many spatial analysis applications in scientific and geographical information systems. Due to the compute-intensive nature of spatial predicate evaluation, spatial join queries can be slow even with a moderate sized dataset. Efficient parallelization of spatial join is therefore essential to achieve acceptable performance for many spatial applications. Technological trends, including the rising core count and increasingly large main memory, hold great promise in this regard. Previous parallel spatial join approaches tried to partition the dataset so that the number of spatial objects in each partition was as equal as possible. They also focused only on the filter step. However, when the more compute-intensive refinement step is included, significant processing skew may arise due to the uneven size of the objects. This processing skew significantly limits the achievable parallel performance of the spatial join queries, as the longest-running spatial partition determines the overall query execution time.\u0000 Our solution is SPINOJA, a skew-resistant parallel in-memory spatial join infrastructure. SPINOJA introduces MOD-Quadtree declustering, which partitions the spatial dataset such that the amount of computation demanded by each partition is equalized and the processing skew is minimized. We compare three work metrics used to create the partitions and three load-balancing strategies to assign the partitions to multiple cores. SPINOJA uses an in-memory column-store to store the spatial tables. Our evaluation shows that SPINOJA outperforms in-memory implementations of previous spatial join approaches by a significant margin and a recently proposed in-memory spatial join algorithm by an order of magnitude.","PeriodicalId":74773,"journal":{"name":"Scientific and statistical database management : International Conference, SSDBM ... : proceedings. International Conference on Scientific and Statistical Database Management","volume":"1 1","pages":"6:1-6:12"},"PeriodicalIF":0.0,"publicationDate":"2014-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90175090","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: 37

Schema matching over relations, attributes, and data values 关系、属性和数据值上的模式匹配

Scientific and statistical database management : International Conference, SSDBM ... : proceedings. International Conference on Scientific and Statistical Database Management Pub Date : 2014-06-30 DOI: 10.1145/2618243.2618248

Aibo Tian, M. Kejriwal, Daniel P. Miranker

{"title":"Schema matching over relations, attributes, and data values","authors":"Aibo Tian, M. Kejriwal, Daniel P. Miranker","doi":"10.1145/2618243.2618248","DOIUrl":"https://doi.org/10.1145/2618243.2618248","url":null,"abstract":"Automatic schema matching algorithms are typically only concerned with finding attribute correspondences. However, real world data integration problems often require matchings whose arguments span all three types of elements in relational databases: relation, attribute and data value. This paper introduces the definitions and semantics of three additional correspondence types concerning both schema and data values. These correspondences cover the higher-order mappings identified in a seminal paper by Krishnamurthy, Litwin, and Kent. It is shown that these correspondences can be automatically translated to tuple generating dependencies (tgds), and thus this research is compatible with data integration applications that leverage tgds.\u0000 Two methods for automatically identifying these correspondences are developed. One requires a limited number of duplicates across data sources. The other is a general instance-based method with no such requirement. Experiments conducted on four real world data sets demonstrate the effectiveness of the methods.","PeriodicalId":74773,"journal":{"name":"Scientific and statistical database management : International Conference, SSDBM ... : proceedings. International Conference on Scientific and Statistical Database Management","volume":"10 1","pages":"28:1-28:12"},"PeriodicalIF":0.0,"publicationDate":"2014-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89378139","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: 9