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We are surrounded by data, numerical, categorical and otherwise, which must to be analyzed and processed to convert it into information that instructs, answers or aids understanding and decision making. Data analysts in many disciplines such as business, education or medicine, are frequently asked to analyze new data sets which are often composed of numerous tables possessing different properties. They try to find completely new correlations between attributes and show new possibilities for users. Action rules mining discusses some of data mining and knowledge discovery principles and then describe representative concepts, methods and algorithms connected with action. The author introduces the formal definition of action rule, notion of a simple association action rule and a representative action rule, the cost of association action rule, and gives a strategy how to construct simple association action rules of a lowest cost. A new approach for generating action rules from datasets with numerical attributes by incorporating a tree classifier and a pruning step based on meta-actions is also presented. In this book we can find fundamental concepts necessary for designing, using and implementing action rules as well. Detailed algorithms are provided with necessary explanation and illustrative examples.
“Mine” is one of the first words babies learn, and by the time we grow up, the idea of ownership seems natural, whether we are buying a cup of coffee or a house. But who controls the space behind your airplane seat: you, reclining, or the squished laptop user behind you? Why is plagiarism wrong, but it’s okay to knock off a recipe or a dress design? And after a snowstorm, why does a chair in the street hold your parking space in Chicago, while in New York you lose both the space and the chair? In Mine!, Michael Heller and James Salzman, two of the world’s leading authorities on ownership, explain these puzzles and many more. Remarkably, they reveal, there are just six simple rules that everyone uses to claim everything. Owners choose the rule that steers us to do what they want. But we can pick differently. This is true not just for airplane seats, but also for battles over digital privacy, climate change, and wealth inequality. Mine! draws on mind-bending, often infuriating, and always fascinating accounts from business, history, courtrooms, and everyday life to reveal how the rules of ownership control our lives and shape our world.
This volume contains the papers selected for presentation at the 17th Inter- tional Symposium on Methodologies for Intelligent Systems (ISMIS 2008), held in York University, Toronto, Canada, May 21–23, 2008. ISMIS is a conference series started in 1986. Held twice every three years, ISMIS provides an inter- tional forum for exchanging scienti?c research and technological achievements in building intelligent systems. Its goal is to achieve a vibrant interchange - tween researchers and practitioners on fundamental and advanced issues related to intelligent systems. ISMIS 2008featureda selectionof latestresearchworkandapplicationsfrom the following areas related to intelligent systems: active media human–computer interaction, autonomic and evolutionary computation, digital libraries, intel- gent agent technology, intelligent information retrieval, intelligent information systems, intelligent language processing, knowledge representation and integ- tion, knowledge discovery and data mining, knowledge visualization, logic for arti?cial intelligence, soft computing, Web intelligence, and Web services. - searchers and developers from 29 countries submitted more than 100 full - pers to the conference. Each paper was rigorously reviewed by three committee members and external reviewers. Out of these submissions, 40% were selected as regular papers and 22% as short papers. ISMIS 2008 also featured three plenary talks given by John Mylopoulos, Jiawei Han and Michael Lowry. They spoke on their recent research in age- oriented software engineering, information network mining, and intelligent so- ware engineering tools, respectively.