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1st PSIP International workshop on Patient Safety through Intelligent Procedures in Medication

作者： Baceanu, Adrian Atasiei, Ionut Chazard, Emmanuel Leroy, Nicolas Ideea Advertising P Ta Mihail Kogalniceanu 1 Bl 1 Sc C Ap 5 Bucharest 050064 Romania Ideea Advertising Bucharest RO-060783 Romania Lille Univ Hosp F-59000 Lille France Region H Hosp Copenhagen Denmark

ISBN: (纸本)9781607504559

An important part of adverse drug events (ADEs) detection is the validation of the clinical cases and the assessment of the decision rules to detect ADEs. For that purpose, a software called "Expert Explorer" has been designed by Ideea Advertising. Anonymized datasets have been extracted from hospitals into a common repository. The tool has 3 main features. (1) It can display hospital stays in a visual and comprehensive way (diagnoses, drugs, lab results, etc.) using tables and pretty charts. (2) It allows designing and executing dashboards in order to generate knowledge about ADEs. (3) It finally allows uploading decision rules obtained from data mining. Experts can then review the rules, the hospital stays that match the rules, and finally give their advice thanks to specialized forms. Then the rules can be validated, invalidated, or improved (knowledge elicitation phase).

关键词： data Mining Association rules database Knowledge Elicitation Web application

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Automatic plan choice validation using performance statistics

Automatic plan choice validation using performance statistic...

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1st International workshop on Testing database Systems, DBTest 2008

作者： Gosalia, Ashit Zhang, Xin Microsoft SQL Server Microsoft Corp. One Microsoft Way Redmond WA 98052 United States

ISBN: (纸本)9781605582337

The query optimizer models data distribution and access paths to make the optimal plan choice for a given query. Sometimes the plan selection is poor because of modeling limitations, outdated statistics, incorrect optimization heuristics, etc. Hence it is useful to examine the plan choice made by the optimizer from an execution perspective and to impose validation rules on the actual execution plan to evaluate plan suitability. This approach treats the optimizer as a black box. The plan validation is based on the queries and data instead of the optimizer implementation details. This paper describes {XPC}, a rule-based tool for Microsoft SQL Server [1] that helps users and developers achieve a better understanding of plan performance. We apply ideas similar to code profilers [2] to examine plan execution performance along with heuristic rules to the actual execution profile and probe for inefficiencies. This paper describes the overview and implementation of {XPC} and presents rules showing how {XPC} is useful in targeting plan performance issues. Copyright 2008 ACM.

关键词： data warehouses

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database servers tailored to improve energy efficiency

Database servers tailored to improve energy efficiency

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1st Edition of the Software Engineering for Tailor-made data Management, SETMDM

作者： Graefe, Goetz Hewlett-Packard Laboratories

ISBN: (纸本)9781595939647

database software can be tailored for specific application domains and their required functionality, for specific hardware and its characteristics, or for other purposes. This brief paper collects issues and techniques required or desirable for making a server-class database management system energy-efficient. The opportunities go far beyond cost functions and general performance improvements. Topics include additional layers in the memory hierarchy, I/O optimizations, data format, scheduling, adaptive query plan execution, and self management in novel ways. This paper represents a challenge rather than a solution. Promising approaches and techniques are indicated throughout, but the challenge is to provide tools for building and tailoring experimental database software that enables research into energy-efficient database management. Copyright © 2008 ACM.

关键词： Cost functions

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Distributed privacy preserving k-means clustering with additive secret sharing 08

Distributed privacy preserving k-means clustering with addit...

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1st International workshop on Privacy and Anonymity in the Information Society, PAIS 2008, Collocated with 11th International Conference on Extending databse Technology, EDBT 2008

作者： Doganay, Mahir Can Pedersen, Thomas B. Saygin, Yücel Savaş, Erkay Levi, Albert Faculty of Engineering and Natural Sciences Sabanci University Istanbul Turkey

ISBN: (纸本)9781595939654

Recent concerns about privacy issues motivated data mining researchers to develop methods for performing data mining while preserving the privacy of individuals. However, the current techniques for privacy preserving data mining suffer from high communication and computation overheads which are prohibitive considering even a modest database size. Furthermore, the proposed techniques have strict assumptions on the involved parties which need to be relaxed in order to reflect the real-world requirements. In this paper we concentrate on a distributed scenario where the data is partitioned vertically over multiple sites and the involved sites would like to perform clustering without revealing their local databases. For this setting, we propose a new protocol for privacy preserving k-means clustering based on additive secret sharing. We show that the new protocol is more secure than the state of the art. Experiments conducted on real and synthetic data sets show that, in realistic scenarios, the communication and computation cost of our protocol is considerably less than the state of the art which is crucial for data mining applications. Copyright 2008 ACM.

关键词： data mining

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Advancing Knowledge Discovery and data Mining

Advancing Knowledge Discovery and Data Mining

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1st International workshop on Knowledge Discovery and data Mining (WKDD 2008)

作者： Qi Luo School of Electrical and Information Engineering Wuhan Institute of Technology Wuhan China Information Engineering School Wuhan University of Science and Technology Wuhan Hubei China

Knowledge discovery and data mining have become areas of growing significance because of the recent increasing demand for KDD techniques, including those used in machine learning, databases, statistics, knowledge acquisition, data visualization, and high performance computing. Knowledge discovery and data mining can be extremely beneficial for the field of Artificial Intelligence in many areas, such as industry, commerce, government, education and so on. The relation between Knowledge and data Mining, and Knowledge Discovery in database (KDD) process are presented in the paper. data mining theory, data mining tasks, data Mining technology and data Mining challenges are also proposed. This is an belief abstract for an invited talk at the workshop.

关键词： data mining Visual databases Machine learning statistics Knowledge acquisition data visualization High performance computing Artificial intelligence Industrial relations Mining industry

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A logic specification and implementation approach for object oriented database security

A logic specification and implementation approach for object...

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1st International workshop on Knowledge Discovery and data Mining

作者： Ni Xianjun Shandong Inst Educ Dept Comp Sci & Technol Jinan 250013 Peoples R China

ISBN: (纸本)9780769530901

This paper is to investigate the implementation of security mechanism in object oriented database system. Formal methods play an essential role in computer security due to its powerful expressiveness and concise syntax and semantics. In this paper, both issues of specification and implementation in database security environment will be considered;and the database security is achieved through the development of an efficient implementation of the specification without compromising its originality and expressiveness.

关键词： Semantics

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Advancing knowledge discovery and data mining

Advancing knowledge discovery and data mining

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1st International workshop on Knowledge Discovery and data Mining

作者： Luo, Qi Wuhan Inst Technol Sch Elect & Informat Engn Wuhan 430073 Peoples R China

ISBN: (纸本)9780769530901

Knowledge discovery and data mining have become areas of growing significance because of the recent increasing demand for KDD techniques, including those used in machine learning, databases, statistics, knowledge acquisition, data visualization, and high performance computing. Knowledge discovery and data mining can be extremely beneficial for the field of Artificial Intelligence in many areas, such as industry, commerce, government, education and so on. The relation between Knowledge and data Mining, and Knowledge Discovery in database (K-DD) process are presented in the paper. data mining theory, data mining tasks, data Mining technology and data Mining challenges are also proposed. This is an belief abstract for an invited talk at the workshop.

关键词： data mining

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A implementation of object oriented database security

A implementation of object oriented database security

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5th ACIS International Conference on Software Engineering Reseach, Management and Applications held in Conjuction with 1st International workshop on Advanced Internet Technology and Applications

作者： Ambhore, Premchand B. Meshram, B. B. Waghmare, V. B. Dr PD Polytech Comp Engn Amravati MS India

ISBN: (纸本)9780769528670

This paper is to address high-level authorization specifications and its efficient implementation in object oriented database scenario. Premchand Ambhore is with higher and technical education, maharashtra state, india, Email:pbambhore@***. The rest of the paper is organized as follows. Section 2 specifies object oriented database system;section 3 incorporates authorization rules into database and section 4 maps the specification into a logic programming language and implements the language. Section 5 concludes the paper. The integration of object-oriented programming concepts with databases is one of the most significant advances in the evolution of database system, therefore the problems involved in providing data security for object oriented databases have been receiving very great attention from researchers. As a matter of fact, data are the most sensitive part of any system and its loss or compromise can have disastrous consequences. We discuss three different types of access: Discretionary access control (DAC), Mandatory access control (MAC) and role. based access control (RBAC) in Relational DBMS and object oriented data bases. We have identified some of the issues and current proposals;current security models in object oriented database systems and outline possible direction issues for future research.

关键词： semantics structural and dynamic data model access control database security authorization policy and logic-based specification

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Domain-oriented data-driven data mining (3DM): Simulation of human knowledge understanding

Domain-oriented data-driven data mining (3DM): Simulation of...

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1st WICI International workshop on Web Intelligence meets Brain Informatics (WImBI 2006)

作者： Wang, Guoyin Chongqing Univ Posts & Telecommun Inst Comp Sci & Technol Chongqing 400065 Peoples R China

ISBN: (纸本)9783540770275

Recent advances in computing, communications, digital storage technologies, and high-throughput data-acquisition technologies, make it possible to gather and store incredible volumes of data. It creates unprecedented opportunities for laxge-scale knowledge discovery from database. data mining (DM) technology has emerged as a means of performing this discovery. It is a useful tool in many fields such as marketing, decision making, etc. There are countless researchers working on designing efficient data mining techniques, methods, and algorithms. Unfortunately, most data mining researchers pay much attention to technique problems for developing data mining models and methods, while little to basic issues of data mining. What is data mining? What is the product of a data mining process? What are we doing in a data mining process? What is the rule we should obey in a data mining process? In this paper, we will address these questions and propose our answers based on a conceptual data mining model. Our answer would be "data mining is a process of knowledge transformation". It is consistent with the process of human knowledge understanding. Based on analysis of the user-driven and "data-driven" data mining approaches proposed by many other researchers, a conceptual knowledge transformation model and a conceptual domain-oriented data-driven data mining (3DM) model are proposed. It integrates user-driven data mining and data-driven data mining into one system. Some future works for developing such a 3DM data mining system are proposed.

关键词： data mining

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A practical solution to supporting oblivious basic operations on dynamic outsourced search trees

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COMPUTER SYstEMS SCIENCE AND ENGINEERING 2006年第1期21卷 53-64页

作者： Dang, TK Middlesex Univ Sch Comp Sci London NW4 4BT England

Search trees have played a fundamental and vital role in both traditional and modern database application domains due to their efficiency in managing the storage and retrieval of data. in the outsourced database service (ODBS) model, outsourced search trees and data are all encrypted and stored at some untrusted server. Security issues in outsourcing database services have increasingly attracted attention in the research community. However, to the best of our knowledge, none of the previous work has radically addressed the problem of preserving privacy for basic operations, which include both search and updates, on outsourced search trees. in this paper, we will discuss security issues in outsourced databases that come together with search trees, and present techniques to ensure privacy in the execution of these trees' basic operations on the untrusted server. By privacy, we mean the outsourced tree structure and data as well as user's queries and their results are all hidden from unauthorized people. Experimental results with real datasets confirm the efficiency of our approach and theoretical analyses.

关键词： dynamic outsourced search trees database services privacy

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