22nd International Conference on Data Engineering (ICDE'06)最新文献_第6页

Learning from Aggregate Views 从聚合视图中学习

22nd International Conference on Data Engineering (ICDE'06) Pub Date : 2006-04-03 DOI: 10.1109/ICDE.2006.86

Bee-Chung Chen, Lei Chen, R. Ramakrishnan, D. Musicant

引用次数: 34

SaveRF: Towards Efficient Relevance Feedback Search SaveRF:迈向高效的相关反馈搜索

22nd International Conference on Data Engineering (ICDE'06) Pub Date : 2006-04-03 DOI: 10.1109/ICDE.2006.132

Heng Tao Shen, B. Ooi, K. Tan

引用次数: 1

Declarative Network Monitoring with an Underprovisioned Query Processor 使用未充分配置的查询处理器的声明性网络监控

22nd International Conference on Data Engineering (ICDE'06) Pub Date : 2006-04-03 DOI: 10.1109/ICDE.2006.46

Frederick Reiss, J. Hellerstein

引用次数: 31

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

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

Foundations of Automated Database Tuning 自动数据库调优的基础

22nd International Conference on Data Engineering (ICDE'06) Pub Date : 2006-04-03 DOI: 10.1109/ICDE.2006.72

Surajit Chaudhuri, G. Weikum

引用次数: 2

Network-Aware Operator Placement for Stream-Processing Systems 流处理系统的网络感知算子配置

22nd International Conference on Data Engineering (ICDE'06) Pub Date : 2006-04-03 DOI: 10.1109/ICDE.2006.105

P. Pietzuch, J. Ledlie, Jeffrey Shneidman, M. Roussopoulos, M. Welsh, M. Seltzer

{"title":"Network-Aware Operator Placement for Stream-Processing Systems","authors":"P. Pietzuch, J. Ledlie, Jeffrey Shneidman, M. Roussopoulos, M. Welsh, M. Seltzer","doi":"10.1109/ICDE.2006.105","DOIUrl":"https://doi.org/10.1109/ICDE.2006.105","url":null,"abstract":"To use their pool of resources efficiently, distributed stream-processing systems push query operators to nodes within the network. Currently, these operators, ranging from simple filters to custom business logic, are placed manually at intermediate nodes along the transmission path to meet application-specific performance goals. Determining placement locations is challenging because network and node conditions change over time and because streams may interact with each other, opening venues for reuse and repositioning of operators. This paper describes a stream-based overlay network (SBON), a layer between a stream-processing system and the physical network that manages operator placement for stream-processing systems. Our design is based on a cost space, an abstract representation of the network and on-going streams, which permits decentralized, large-scale multi-query optimization decisions. We present an evaluation of the SBON approach through simulation, experiments on PlanetLab, and an integration with Borealis, an existing stream-processing engine. Our results show that an SBON consistently improves network utilization, provides low stream latency, and enables dynamic optimization at low engineering cost.","PeriodicalId":6819,"journal":{"name":"22nd International Conference on Data Engineering (ICDE'06)","volume":"122 1","pages":"49-49"},"PeriodicalIF":0.0,"publicationDate":"2006-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83649866","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: 474

Approximation Techniques for Indexing the Earth Mover’s Distance in Multimedia Databases 多媒体数据库中推土机距离索引的近似技术

22nd International Conference on Data Engineering (ICDE'06) Pub Date : 2006-04-03 DOI: 10.1109/ICDE.2006.25

I. Assent, Andrea Wenning, T. Seidl

引用次数: 82

Mining Actionable Patterns by Role Models 通过角色模型挖掘可操作的模式

22nd International Conference on Data Engineering (ICDE'06) Pub Date : 2006-04-03 DOI: 10.1109/ICDE.2006.96

Ke Wang, Yuelong Jiang, A. Tuzhilin

引用次数: 61

Automatic Sales Lead Generation from Web Data 从网络数据自动生成销售线索

22nd International Conference on Data Engineering (ICDE'06) Pub Date : 2006-04-03 DOI: 10.1109/ICDE.2006.28

Ganesh Ramakrishnan, Sachindra Joshi, Sumit Negi, R. Krishnapuram, S. Balakrishnan

{"title":"Automatic Sales Lead Generation from Web Data","authors":"Ganesh Ramakrishnan, Sachindra Joshi, Sumit Negi, R. Krishnapuram, S. Balakrishnan","doi":"10.1109/ICDE.2006.28","DOIUrl":"https://doi.org/10.1109/ICDE.2006.28","url":null,"abstract":"Speed to market is critical to companies that are driven by sales in a competitive market. The earlier a potential customer can be approached in the decision making process of a purchase, the higher are the chances of converting that prospect into a customer. Traditional methods to identify sales leads such as company surveys and direct marketing are manual, expensive and not scalable. Over the past decade the World Wide Web has grown into an information-mesh, with most important facts being reported through Web sites. Several news papers, press releases, trade journals, business magazines and other related sources are on-line. These sources could be used to identify prospective buyers automatically. In this paper, we present a system called ETAP (Electronic Trigger Alert Program) that extracts trigger events from Web data that help in identifying prospective buyers. Trigger events are events of corporate relevance and indicative of the propensity of companies to purchase new products associated with these events. Examples of trigger events are change in management, revenue growth and mergers & acquisitions. The unstructured nature of information makes the extraction task of trigger events difficult. We pose the problem of trigger events extraction as a classification problem and develop methods for learning trigger event classifiers using existing classification methods. We present methods to automatically generate the training data required to learn the classifiers. We also propose a method of feature abstraction that uses named entity recognition to solve the problem of data sparsity. We score and rank the trigger events extracted from ETAP for easy browsing. Our experiments show the effectiveness of the method and thus establish the feasibility of automatic sales lead generation using the Web data.","PeriodicalId":6819,"journal":{"name":"22nd International Conference on Data Engineering (ICDE'06)","volume":"67 1","pages":"101-101"},"PeriodicalIF":0.0,"publicationDate":"2006-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90276794","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