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Proceedings -- Parallel Computing.
Many organizations have an urgent need of mining their multiple databases inherently distributed in branches (distributed data). In particular, as the Web is rapidly becoming an information flood, individuals and organizations can take into account low-cost information and knowledge on the Internet when making decisions. How to efficiently identify quality knowledge from different data sources has become a significant challenge. This challenge has attracted a great many researchers including the au thors who have developed a local pattern analysis, a new strategy for dis covering some kinds of potentially useful patterns that cannot be mined in traditional multi-database mining techniques. Local pattern analysis deliv ers high-performance pattern discovery from multiple databases. There has been considerable progress made on multi-database mining in such areas as hierarchical meta-learning, collective mining, database classification, and pe culiarity discovery. While these techniques continue to be future topics of interest concerning multi-database mining, this book focuses on these inter esting issues under the framework of local pattern analysis. The book is intended for researchers and students in data mining, dis tributed data analysis, machine learning, and anyone else who is interested in multi-database mining. It is also appropriate for use as a text supplement for broader courses that might also involve knowledge discovery in databases and data mining.
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The objective of program analysis is to automatically determine the p- perties of a program. Tools of software development, such as compilers, p- formance estimators, debuggers, reverse-engineering tools, program veri?- tion/testing/proving systems, program comprehension systems, and program specializationtoolsarelargelydependentonprogramanalysis. Advancedp- gram analysis can: help to ?nd program errors; detect and tune performan- critical code regions; ensure assumed constraints on data are not violated; tailor a generic program to suit a speci?c application; reverse-engineer so- ware modules, etc. A prominent program analysis technique is symbolic a- lysis, which has attracted substantial attention for many years as it is not dependent on executing a program to examine the semantics of a program, and it can yield very elegant formulations of many analyses. Moreover, the complexity of symbolic analysis can be largely independent of the input data size of a program and of the size of the machine on which the program is being executed. In this book we present novel symbolic control and data ?ow repres- tation techniques as well as symbolic techniques and algorithms to analyze and optimize programs. Program contexts which de?ne a new symbolic - scription of program semantics for control and data ?ow analysis are at the center of our approach. We have solved a number of problems encountered in program analysis by using program contexts. Our solution methods are e?cient, versatile, uni?ed, and more general (they cope with regular and irregular codes) than most existing methods.
This monograph addresses four critical software development aspects for the engineering and execution of applications on parallel and Grid architectures. A new directive-based language called ZEN is proposed for compact specification of wide value ranges of interest for arbitrary application parameters. The monograph contributes to various research areas related to integrated tool development for efficient engineering and high performance execution of scientific applications in Grid environments.

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