22nd International Conference on Data Engineering (ICDE'06)最新文献_第4页

Provable Security for Outsourcing Database Operations 外包数据库操作的可验证安全性

22nd International Conference on Data Engineering (ICDE'06) Pub Date : 2006-04-03 DOI: 10.1109/ICDE.2006.121

S. Evdokimov, M. Fischmann, O. Günther

引用次数: 35

Searching Local Information in Mobile Databases 在移动数据库中搜索本地信息

22nd International Conference on Data Engineering (ICDE'06) Pub Date : 2006-04-03 DOI: 10.1109/ICDE.2006.135

O. Wolfson, Bo Xu, Huabei Yin, Hu Cao

引用次数: 8

Counting at Large: Efficient Cardinality Estimation in Internet-Scale Data Networks 大规模计数:互联网规模数据网络中的有效基数估计

22nd International Conference on Data Engineering (ICDE'06) Pub Date : 2006-04-03 DOI: 10.1109/ICDE.2006.44

Nikos Ntarmos, P. Triantafillou, G. Weikum

{"title":"Counting at Large: Efficient Cardinality Estimation in Internet-Scale Data Networks","authors":"Nikos Ntarmos, P. Triantafillou, G. Weikum","doi":"10.1109/ICDE.2006.44","DOIUrl":"https://doi.org/10.1109/ICDE.2006.44","url":null,"abstract":"Counting in general, and estimating the cardinality of (multi-) sets in particular, is highly desirable for a large variety of applications, representing a foundational block for the efficient deployment and access of emerging internetscale information systems. Examples of such applications range from optimizing query access plans in internet-scale databases, to evaluating the significance (rank/score) of various data items in information retrieval applications. The key constraints that any acceptable solution must satisfy are: (i) efficiency: the number of nodes that need be contacted for counting purposes must be small in order to enjoy small latency and bandwidth requirements; (ii) scalability, seemingly contradicting the efficiency goal: arbitrarily large numbers of nodes nay need to add elements to a (multi-) set, which dictates the need for a highly distributed solution, avoiding server-based scalability, bottleneck, and availability problems; (iii) access and storage load balancing: counting and related overhead chores should be distributed fairly to the nodes of the network; (iv) accuracy: tunable, robust (in the presence of dynamics and failures) and highly accurate cardinality estimation; (v) simplicity and ease of integration: special, solution-specific indexing structures should be avoided. In this paper, first we contribute a highly-distributed, scalable, efficient, and accurate (multi-) set cardinality estimator. Subsequently, we show how to use our solution to build and maintain histograms, which have been a basic building block for query optimization for centralized databases, facilitating their porting into the realm of internet-scale data networks.","PeriodicalId":6819,"journal":{"name":"22nd International Conference on Data Engineering (ICDE'06)","volume":"37 1","pages":"40-40"},"PeriodicalIF":0.0,"publicationDate":"2006-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88604567","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: 39

Detecting Duplicates in Complex XML Data 检测复杂XML数据中的重复项

22nd International Conference on Data Engineering (ICDE'06) Pub Date : 2006-04-03 DOI: 10.1109/ICDE.2006.49

Melanie Herschel, Felix Naumann

引用次数: 33

RDF/RDFS-based Relational Database Integration 基于RDF/ rdfs的关系数据库集成

22nd International Conference on Data Engineering (ICDE'06) Pub Date : 2006-04-03 DOI: 10.1109/ICDE.2006.127

Huajun Chen, Zhaohui Wu, Heng Wang, Yuxin Mao

引用次数: 67

Simultaneous Pipelining in QPipe: Exploiting Work Sharing Opportunities Across Queries QPipe中的同步流水线:利用跨查询的工作共享机会

22nd International Conference on Data Engineering (ICDE'06) Pub Date : 2006-04-03 DOI: 10.1109/ICDE.2006.138

Kun Gao, S. Harizopoulos, I. Pandis, Vladislav Shkapenyuk, A. Ailamaki

引用次数: 12

Characterizing and Exploiting Reference Locality in Data Stream Applications 数据流应用中引用局部性的刻画和利用

22nd International Conference on Data Engineering (ICDE'06) Pub Date : 2006-04-03 DOI: 10.1109/ICDE.2006.33

Feifei Li, Ching Chang, G. Kollios, Azer Bestavros

引用次数: 26

DREAM: A Data Replication Technique for Real-Time Mobile Ad-hoc Network Databases DREAM:实时移动Ad-hoc网络数据库的数据复制技术

22nd International Conference on Data Engineering (ICDE'06) Pub Date : 2006-04-03 DOI: 10.1109/ICDE.2006.52

P. Padmanabhan, L. Gruenwald

引用次数: 25

The Gauss-Tree: Efficient Object Identification in Databases of Probabilistic Feature Vectors 高斯树:概率特征向量数据库中有效的目标识别

22nd International Conference on Data Engineering (ICDE'06) Pub Date : 2006-04-03 DOI: 10.1109/ICDE.2006.159

C. Böhm, A. Pryakhin, Matthias Schubert

{"title":"The Gauss-Tree: Efficient Object Identification in Databases of Probabilistic Feature Vectors","authors":"C. Böhm, A. Pryakhin, Matthias Schubert","doi":"10.1109/ICDE.2006.159","DOIUrl":"https://doi.org/10.1109/ICDE.2006.159","url":null,"abstract":"In applications of biometric databases the typical task is to identify individuals according to features which are not exactly known. Reasons for this inexactness are varying measuring techniques or environmental circumstances. Since these circumstances are not necessarily the same when determining the features for different individuals, the exactness might strongly vary between the individuals as well as between the features. To identify individuals, similarity search on feature vectors is applicable, but even the use of adaptable distance measures is not capable to handle objects having an individual level of exactness. Therefore, we develop a comprehensive probabilistic theory in which uncertain observations are modeled by probabilistic feature vectors (pfv), i.e. feature vectors where the conventional feature values are replaced by Gaussian probability distribution functions. Each feature value of each object is complemented by a variance value indicating its uncertainty. We define two types of identification queries, k-mostlikely identification and threshold identification. For efficient query processing, we propose a novel index structure, the Gauss-tree. Our experimental evaluation demonstrates that pfv stored in a Gauss-tree significantly improve the result quality compared to traditional feature vectors. Additionally, we show that the Gauss-tree significantly speeds up query times compared to competitive methods.","PeriodicalId":6819,"journal":{"name":"22nd International Conference on Data Engineering (ICDE'06)","volume":"11 1","pages":"9-9"},"PeriodicalIF":0.0,"publicationDate":"2006-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73792085","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: 124

Collaborative Business Process Support in IHE XDS through ebXML Business Processes 通过ebXML业务流程支持IHE XDS中的协作业务流程

22nd International Conference on Data Engineering (ICDE'06) Pub Date : 2006-04-03 DOI: 10.1109/ICDE.2006.39

A. Dogac, V. Bicer, Alper Okcan

{"title":"Collaborative Business Process Support in IHE XDS through ebXML Business Processes","authors":"A. Dogac, V. Bicer, Alper Okcan","doi":"10.1109/ICDE.2006.39","DOIUrl":"https://doi.org/10.1109/ICDE.2006.39","url":null,"abstract":"Currently, clinical information is stored in all kinds of proprietary formats through a multitude of medical information systems available on the market. This results in a severe interoperability problem in sharing electronic healthcare records. To address this problem, an industry initiative, called \"Integrating Healthcare Enterprise (IHE)\" has specified the \"Cross Enterprise Document Sharing (XDS)\" Profile to store healthcare documents in an ebXML registry/ repository to facilitate their sharing. Through a separate effort, IHE has also defined interdepartmental Workflow Profiles to identify the transactions required to integrate information flow among several information systems. Although the clinical documents stored in XDS registries are obtained as a result of executing these workflows, IHE has not yet specified collaborative healthcare processes for the XDS. Hence, there is no way to track the workflows in XDS and the clinical documents produced through the workflows are manually inserted into the registry/ repository. Given that IHE XDS is using the ebXML architecture, the most natural way to integrate IHE Workflow Profiles to IHE XDS is using ebXML Business Processes (ebBP). In this paper, we describe the implementation of an enhanced IHE architecture demonstrating how ebXML Business Processes, IHE Workflow Profiles and the IHE XDS architecture can all be integrated to provide collaborative business process support in the healthcare domain.","PeriodicalId":6819,"journal":{"name":"22nd International Conference on Data Engineering (ICDE'06)","volume":"6 1","pages":"91-91"},"PeriodicalIF":0.0,"publicationDate":"2006-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75104754","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