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The Metropolitan Parliamentary Reform Association
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Year: 1842 Publisher: [England s.n.

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Laws and regulations of the Trades' Newspaper Association
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Year: 1825 Publisher: London Printed for the Trades, by J. Limbird

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The First London Co-operative Association : its objects and laws.
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Year: 1829 Publisher: [England s.n.]

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Address to the inhabitants of the parish of Hackney : together with the rules of Hackney Parochial Association, for the correction and prevention of abuses.
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Year: 1833 Publisher: [England s.n.]

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The laws, rules, and orders, to be observed by the Friendly and Brotherly Association
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Year: 1770 Publisher: London Printed by Thomas Baldwin

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Business intelligence and data mining
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ISBN: 1631571214 Year: 2015 Publisher: New York, New York (222 East 46th Street, New York, NY 10017) : Business Expert Press,

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Business is the act of doing something productive to serve someone's needs, and thus earn a living, and make the world a better place. Business activities are recorded on paper or using electronic media, and then these records become data. There is more data from customers' responses and on the industry as a whole. All this data can be analyzed and mined using special tools and techniques to generate patterns and intelligence, which reflect how the business is functioning. These ideas can then be fed back into the business so that it can evolve to become more effective and efficient in serving customer needs. And the cycle continues on. Business intelligence includes tools and techniques for data gathering, analysis, and visualization for helping with executive decision making in any industry. Data mining includes statistical and machine-learning techniques to build decision-making models from raw data. Data mining techniques covered in this book include decision trees, regression, artificial neural networks, cluster analysis, and many more. Text mining, web mining, and big data are also covered in an easy way. A primer on data modeling is included for those uninitiated in this topic.


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Action rules mining
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ISBN: 3642356494 3642356508 Year: 2013 Publisher: Berlin ; New York : Springer,

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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.


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Observational calculi and association rules
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ISBN: 3642117368 3642117376 Year: 2013 Publisher: Heidelberg ; New York : Springer-Verlag,

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Observational calculi were introduced in the 1960’s as a tool of logic of discovery. Formulas of observational calculi correspond to assertions on analysed data. Truthfulness of suitable assertions can lead to acceptance of new scientific hypotheses. The general goal was to automate the process of discovery of scientific knowledge using mathematical logic and statistics. The GUHA method for producing true formulas of observational calculi relevant to the given problem of scientific discovery was developed. Theoretically interesting and practically important results on observational calculi were achieved. Special attention was paid to formulas - couples of Boolean attributes derived from columns of the analysed data matrix. Association rules introduced in the 1990’s can be seen as a special case of such formulas. New results on logical calculi and association rules were achieved. They can be seen as a logic of association rules. This can contribute to solving contemporary challenging problems of data mining research and practice. The book covers thoroughly the logic of association rules and puts it into the context of current research in data mining. Examples of applications of theoretical results to real problems are presented. New open problems and challenges are listed. Overall, the book is a valuable source of information for researchers as well as for teachers and students interested in data mining.


Book
Clustering, association and classification
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ISBN: 3642231659 3642231667 3642430937 Year: 2012 Publisher: Berlin : Springer,

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Data mining is one of the most rapidly growing research areas in computer science and statistics. In Volume 1of this three volume series, we have brought together contributions from some of the most prestigious researchers in the fundamental data mining tasks of clustering, association and classification. Each of the chapters is self contained. Theoreticians and applied scientists/ engineers will find this volume valuable. Additionally, it provides a sourcebook for graduate students interested in the current direction of research in these aspects of data mining.


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Edge Computing for Internet of Things
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Year: 2022 Publisher: Basel MDPI - Multidisciplinary Digital Publishing Institute

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The Internet-of-Things is becoming an established technology, with devices being deployed in homes, workplaces, and public areas at an increasingly rapid rate. IoT devices are the core technology of smart-homes, smart-cities, intelligent transport systems, and promise to optimise travel, reduce energy usage and improve quality of life. With the IoT prevalence, the problem of how to manage the vast volumes of data, wide variety and type of data generated, and erratic generation patterns is becoming increasingly clear and challenging. This Special Issue focuses on solving this problem through the use of edge computing. Edge computing offers a solution to managing IoT data through the processing of IoT data close to the location where the data is being generated. Edge computing allows computation to be performed locally, thus reducing the volume of data that needs to be transmitted to remote data centres and Cloud storage. It also allows decisions to be made locally without having to wait for Cloud servers to respond.

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