K. Whang, Min-Jae Lee, Jae-Gil Lee, Min-Soo Kim, Wook-Shin Han
We propose the notion of tight-coupling [K. Whang et al., (1999)] to add new data types into the DBMS engine. In this paper, we introduce the Odysseus ORDBMS and present its tightly-coupled IR features (US patented). We demonstrate a Web search engine capable of managing 20 million Web pages in a non-parallel configuration using Odysseus.
我们提出了紧密耦合的概念[K]。Whang et al.，(1999)]向DBMS引擎中添加新的数据类型。本文介绍了Odysseus ORDBMS，并介绍了其紧耦合IR特性(美国专利)。我们将演示一个Web搜索引擎，它能够使用奥德修斯在非并行配置中管理2000万个Web页面。
{"title":"Odysseus: a high-performance ORDBMS tightly-coupled with IR features","authors":"K. Whang, Min-Jae Lee, Jae-Gil Lee, Min-Soo Kim, Wook-Shin Han","doi":"10.1109/ICDE.2005.95","DOIUrl":"https://doi.org/10.1109/ICDE.2005.95","url":null,"abstract":"We propose the notion of tight-coupling [K. Whang et al., (1999)] to add new data types into the DBMS engine. In this paper, we introduce the Odysseus ORDBMS and present its tightly-coupled IR features (US patented). We demonstrate a Web search engine capable of managing 20 million Web pages in a non-parallel configuration using Odysseus.","PeriodicalId":297231,"journal":{"name":"21st International Conference on Data Engineering (ICDE'05)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121487947","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}
A reverse nearest neighbor query returns the data objects that have a query point as their nearest neighbor. Although such queries have been studied quite extensively in Euclidean spaces, there is no previous work in the context of large graphs. In this paper, we propose algorithms and optimization techniques for RNN queries by utilizing some characteristics of networks.
{"title":"Reverse nearest neighbors in large graphs","authors":"Man Lung Yiu, D. Papadias, N. Mamoulis, Yufei Tao","doi":"10.1109/ICDE.2005.124","DOIUrl":"https://doi.org/10.1109/ICDE.2005.124","url":null,"abstract":"A reverse nearest neighbor query returns the data objects that have a query point as their nearest neighbor. Although such queries have been studied quite extensively in Euclidean spaces, there is no previous work in the context of large graphs. In this paper, we propose algorithms and optimization techniques for RNN queries by utilizing some characteristics of networks.","PeriodicalId":297231,"journal":{"name":"21st International Conference on Data Engineering (ICDE'05)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122388789","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}
Data de-identification reconciles the demand for release of data for research purposes and the demand for privacy from individuals. This paper proposes and evaluates an optimization algorithm for the powerful de-identification procedure known as k-anonymization. A k-anonymized dataset has the property that each record is indistinguishable from at least k - 1 others. Even simple restrictions of optimized k-anonymity are NP-hard, leading to significant computational challenges. We present a new approach to exploring the space of possible anonymizations that tames the combinatorics of the problem, and develop data-management strategies to reduce reliance on expensive operations such as sorting. Through experiments on real census data, we show the resulting algorithm can find optimal k-anonymizations under two representative cost measures and a wide range of k. We also show that the algorithm can produce good anonymizations in circumstances where the input data or input parameters preclude finding an optimal solution in reasonable time. Finally, we use the algorithm to explore the effects of different coding approaches and problem variations on anonymization quality and performance. To our knowledge, this is the first result demonstrating optimal k-anonymization of a non-trivial dataset under a general model of the problem.
{"title":"Data privacy through optimal k-anonymization","authors":"R. Bayardo, R. Agrawal","doi":"10.1109/ICDE.2005.42","DOIUrl":"https://doi.org/10.1109/ICDE.2005.42","url":null,"abstract":"Data de-identification reconciles the demand for release of data for research purposes and the demand for privacy from individuals. This paper proposes and evaluates an optimization algorithm for the powerful de-identification procedure known as k-anonymization. A k-anonymized dataset has the property that each record is indistinguishable from at least k - 1 others. Even simple restrictions of optimized k-anonymity are NP-hard, leading to significant computational challenges. We present a new approach to exploring the space of possible anonymizations that tames the combinatorics of the problem, and develop data-management strategies to reduce reliance on expensive operations such as sorting. Through experiments on real census data, we show the resulting algorithm can find optimal k-anonymizations under two representative cost measures and a wide range of k. We also show that the algorithm can produce good anonymizations in circumstances where the input data or input parameters preclude finding an optimal solution in reasonable time. Finally, we use the algorithm to explore the effects of different coding approaches and problem variations on anonymization quality and performance. To our knowledge, this is the first result demonstrating optimal k-anonymization of a non-trivial dataset under a general model of the problem.","PeriodicalId":297231,"journal":{"name":"21st International Conference on Data Engineering (ICDE'05)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122838802","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}
This paper describes a novel filter based replication model for lightweight directory access protocol (LDAP) directories. Instead of replicating entire subtrees from the directory information tree (DIT), only entries matching a filter specification are replicated Advantages of the filter based replication framework over existing subtree based mechanisms have been demonstrated for a real enterprise directory using real workloads.
{"title":"Filter based directory replication and caching","authors":"Apurva Kumar","doi":"10.1109/ICDE.2005.67","DOIUrl":"https://doi.org/10.1109/ICDE.2005.67","url":null,"abstract":"This paper describes a novel filter based replication model for lightweight directory access protocol (LDAP) directories. Instead of replicating entire subtrees from the directory information tree (DIT), only entries matching a filter specification are replicated Advantages of the filter based replication framework over existing subtree based mechanisms have been demonstrated for a real enterprise directory using real workloads.","PeriodicalId":297231,"journal":{"name":"21st International Conference on Data Engineering (ICDE'05)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128075533","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}
Advanced database application areas, such as computer aided design, office automation, digital libraries, data-mining as well as hypertext and multimedia systems need to handle complex data structures with set-valued attributes, which can be represented as bit strings, called signatures. A set of signatures can be stored in a file, called a signature file. In this paper, we propose a new method to organize a signature file into a tree structure, called a signature tree, to speed up the signature file scanning and query evaluation.
{"title":"On the signature trees and balanced signature trees","authors":"Yangjun Chen","doi":"10.1109/ICDE.2005.99","DOIUrl":"https://doi.org/10.1109/ICDE.2005.99","url":null,"abstract":"Advanced database application areas, such as computer aided design, office automation, digital libraries, data-mining as well as hypertext and multimedia systems need to handle complex data structures with set-valued attributes, which can be represented as bit strings, called signatures. A set of signatures can be stored in a file, called a signature file. In this paper, we propose a new method to organize a signature file into a tree structure, called a signature tree, to speed up the signature file scanning and query evaluation.","PeriodicalId":297231,"journal":{"name":"21st International Conference on Data Engineering (ICDE'05)","volume":"144 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134222456","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}
The demand for the secondary use of medical data is increasing steadily to allow for the provision of better quality health care. Two important issues pertaining to this sharing of data have to be addressed: one is the privacy protection for individuals referred to in the data; the other is copyright protection over the data. In this paper, we present a unified framework that seamlessly combines techniques of binning and digital watermarking to attain the dual goals of privacy and copyright protection. Our binning method is built upon an earlier approach of generalization and suppression by allowing a broader concept of generalization. To ensure data usefulness, we propose constraining binning by usage metrics that define maximal allowable information loss, and the metrics can be enforced off-line. Our watermarking algorithm watermarks the binned data in a hierarchical manner by leveraging on the very nature of the data. The method is resilient to the generalization attack that is specific to the binned data, as well as other attacks intended to destroy the inserted mark. We prove that watermarking could not adversely interfere with binning, and implemented the framework. Experiments were conducted, and the results show the robustness of the proposed framework.
{"title":"Privacy and ownership preserving of outsourced medical data","authors":"E. Bertino, B. Ooi, Yanjiang Yang, R. Deng","doi":"10.1109/ICDE.2005.111","DOIUrl":"https://doi.org/10.1109/ICDE.2005.111","url":null,"abstract":"The demand for the secondary use of medical data is increasing steadily to allow for the provision of better quality health care. Two important issues pertaining to this sharing of data have to be addressed: one is the privacy protection for individuals referred to in the data; the other is copyright protection over the data. In this paper, we present a unified framework that seamlessly combines techniques of binning and digital watermarking to attain the dual goals of privacy and copyright protection. Our binning method is built upon an earlier approach of generalization and suppression by allowing a broader concept of generalization. To ensure data usefulness, we propose constraining binning by usage metrics that define maximal allowable information loss, and the metrics can be enforced off-line. Our watermarking algorithm watermarks the binned data in a hierarchical manner by leveraging on the very nature of the data. The method is resilient to the generalization attack that is specific to the binned data, as well as other attacks intended to destroy the inserted mark. We prove that watermarking could not adversely interfere with binning, and implemented the framework. Experiments were conducted, and the results show the robustness of the proposed framework.","PeriodicalId":297231,"journal":{"name":"21st International Conference on Data Engineering (ICDE'05)","volume":"152 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132299152","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}
The query optimizer of a database system is confronted with two aspects when handling user-defined functions (UDFs) in query predicates: the vast differences in evaluation costs between UDFs (and other functions) and multiple calls of the same (expensive) UDF The former is dealt with by ordering the evaluation of the predicates optimally, the latter by identifying common subexpressions and thereby avoiding costly recomputation. Current approaches order n predicates optimally (neglecting factorization) in O(nlogn). Their result may deviate significantly from the optimal solution under factorization. We formalize the problem of finding optimal orderings under factorization and prove that it is NP-hard. Furthermore, we show how to improve on the run time of the brute-force algorithm (which computes all possible orderings) by presenting different enhanced algorithms. Although in the worst case these algorithms obviously still behave exponentially, our experiments demonstrate that for real-life examples their performance is much better.
{"title":"On the optimal ordering of maps and selections under factorization","authors":"Thomas Neumann, S. Helmer, G. Moerkotte","doi":"10.1109/ICDE.2005.97","DOIUrl":"https://doi.org/10.1109/ICDE.2005.97","url":null,"abstract":"The query optimizer of a database system is confronted with two aspects when handling user-defined functions (UDFs) in query predicates: the vast differences in evaluation costs between UDFs (and other functions) and multiple calls of the same (expensive) UDF The former is dealt with by ordering the evaluation of the predicates optimally, the latter by identifying common subexpressions and thereby avoiding costly recomputation. Current approaches order n predicates optimally (neglecting factorization) in O(nlogn). Their result may deviate significantly from the optimal solution under factorization. We formalize the problem of finding optimal orderings under factorization and prove that it is NP-hard. Furthermore, we show how to improve on the run time of the brute-force algorithm (which computes all possible orderings) by presenting different enhanced algorithms. Although in the worst case these algorithms obviously still behave exponentially, our experiments demonstrate that for real-life examples their performance is much better.","PeriodicalId":297231,"journal":{"name":"21st International Conference on Data Engineering (ICDE'05)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117187879","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}
Many decision support applications are characterized by several features: (1) the query is typically based on multiple criteria; (2) there is no single optimal answer (or answer set); (3) because of (2), users typically look for satisfying answers; (4) for the same query, different users, dictated by their personal preferences, may find different answers meeting their needs. As such, it is important for the DBMS to present all interesting answers that may fulfill a user's need. In this article, we focus on the set of interesting answers called the skyline. Given a set of points, the skyline comprises the points that are not dominated by other points. A point dominates another point if it is as good or better in all dimensions and better in at least one dimension. We address the novel and important problem of evaluating skyline queries involving partially-ordered attribute domains.
{"title":"Efficient processing of skyline queries with partially-ordered domains","authors":"C. Chan, P. Eng, K. Tan","doi":"10.1109/ICDE.2005.60","DOIUrl":"https://doi.org/10.1109/ICDE.2005.60","url":null,"abstract":"Many decision support applications are characterized by several features: (1) the query is typically based on multiple criteria; (2) there is no single optimal answer (or answer set); (3) because of (2), users typically look for satisfying answers; (4) for the same query, different users, dictated by their personal preferences, may find different answers meeting their needs. As such, it is important for the DBMS to present all interesting answers that may fulfill a user's need. In this article, we focus on the set of interesting answers called the skyline. Given a set of points, the skyline comprises the points that are not dominated by other points. A point dominates another point if it is as good or better in all dimensions and better in at least one dimension. We address the novel and important problem of evaluating skyline queries involving partially-ordered attribute domains.","PeriodicalId":297231,"journal":{"name":"21st International Conference on Data Engineering (ICDE'05)","volume":"107 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116982058","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}
Graham Cormode, Flip Korn, S. Muthukrishnan, D. Srivastava
Skew is prevalent in many data sources such as IP traffic streams. To continually summarize the distribution of such data, a high-biased set of quantiles (e.g., 50th, 90th and 99th percentiles) with finer error guarantees at higher ranks (e.g., errors of 5, 1 and 0.1 percent, respectively) is more useful than uniformly distributed quantiles (e.g., 25th, 50th and 75th percentiles) with uniform error guarantees. In this paper, we address the following two problems. First, can we compute quantiles with finer error guarantees for the higher ranks of the data distribution effectively using less space and computation time than computing all quantiles uniformly at the finest error? Second, if specific quantiles and their error bounds are requested a priori, can the necessary space usage and computation time be reduced? We answer both questions in the affirmative by formalizing them as the "high-biased" and the "targeted" quantiles problems, respectively, and presenting algorithms with provable guarantees, that perform significantly better than previously known solutions for these problems. We implemented our algorithms in the Gigascope data stream management system, and evaluated alternate approaches for maintaining the relevant summary structures. Our experimental results on real and synthetic IP data streams complement our theoretical analyses, and highlight the importance of lightweight, non-blocking implementations when maintaining summary structures over highspeed data streams.
{"title":"Effective computation of biased quantiles over data streams","authors":"Graham Cormode, Flip Korn, S. Muthukrishnan, D. Srivastava","doi":"10.1109/ICDE.2005.55","DOIUrl":"https://doi.org/10.1109/ICDE.2005.55","url":null,"abstract":"Skew is prevalent in many data sources such as IP traffic streams. To continually summarize the distribution of such data, a high-biased set of quantiles (e.g., 50th, 90th and 99th percentiles) with finer error guarantees at higher ranks (e.g., errors of 5, 1 and 0.1 percent, respectively) is more useful than uniformly distributed quantiles (e.g., 25th, 50th and 75th percentiles) with uniform error guarantees. In this paper, we address the following two problems. First, can we compute quantiles with finer error guarantees for the higher ranks of the data distribution effectively using less space and computation time than computing all quantiles uniformly at the finest error? Second, if specific quantiles and their error bounds are requested a priori, can the necessary space usage and computation time be reduced? We answer both questions in the affirmative by formalizing them as the \"high-biased\" and the \"targeted\" quantiles problems, respectively, and presenting algorithms with provable guarantees, that perform significantly better than previously known solutions for these problems. We implemented our algorithms in the Gigascope data stream management system, and evaluated alternate approaches for maintaining the relevant summary structures. Our experimental results on real and synthetic IP data streams complement our theoretical analyses, and highlight the importance of lightweight, non-blocking implementations when maintaining summary structures over highspeed data streams.","PeriodicalId":297231,"journal":{"name":"21st International Conference on Data Engineering (ICDE'05)","volume":"195 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116832987","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}
In the ADEPT project we have been working on the design and implementation of next generation process management software. Based on a conceptual framework for dynamic process changes, on novel process support functions, and on advanced implementation concepts, the developed system enables the realization of adaptive, process-aware information systems (PAIS). Basically, process changes can take place at the type as well as the instance level: changes of single process instances may have to be carried out in an ad-hoc manner and must not affect system robustness and consistency. Process type changes, in turn, must be quickly accomplished in order to adapt the PAIS to business process changes. ADEPT2 offers powerful concepts for modeling, analyzing, and verifying process schemes. Particularly, it ensures schema correctness, like the absence of deadlock-causing cycles or erroneous data flows. This, in turn, constitutes an important prerequisite for dynamic process changes as well. ADEPT2 supports both ad-hoc changes of single process instances and the propagation of process type changes to running instances.
{"title":"Adaptive process management with ADEPT2","authors":"M. Reichert, S. Rinderle-Ma, U. Kreher, P. Dadam","doi":"10.1109/ICDE.2005.17","DOIUrl":"https://doi.org/10.1109/ICDE.2005.17","url":null,"abstract":"In the ADEPT project we have been working on the design and implementation of next generation process management software. Based on a conceptual framework for dynamic process changes, on novel process support functions, and on advanced implementation concepts, the developed system enables the realization of adaptive, process-aware information systems (PAIS). Basically, process changes can take place at the type as well as the instance level: changes of single process instances may have to be carried out in an ad-hoc manner and must not affect system robustness and consistency. Process type changes, in turn, must be quickly accomplished in order to adapt the PAIS to business process changes. ADEPT2 offers powerful concepts for modeling, analyzing, and verifying process schemes. Particularly, it ensures schema correctness, like the absence of deadlock-causing cycles or erroneous data flows. This, in turn, constitutes an important prerequisite for dynamic process changes as well. ADEPT2 supports both ad-hoc changes of single process instances and the propagation of process type changes to running instances.","PeriodicalId":297231,"journal":{"name":"21st International Conference on Data Engineering (ICDE'05)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115485948","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}
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