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Author: Laleh Jalali
Publisher: Morgan & Claypool
ISBN: 1450384854
Category : Computers
Languages : en
Pages : 162
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Book Description
This book introduces the concept of Event Mining for building explanatory models from analyses of correlated data. Such a model may be used as the basis for predictions and corrective actions. The idea is to create, via an iterative process, a model that explains causal relationships in the form of structural and temporal patterns in the data. The first phase is the data-driven process of hypothesis formation, requiring the analysis of large amounts of data to find strong candidate hypotheses. The second phase is hypothesis testing, wherein a domain expert’s knowledge and judgment is used to test and modify the candidate hypotheses. The book is intended as a primer on Event Mining for data-enthusiasts and information professionals interested in employing these event-based data analysis techniques in diverse applications. The reader is introduced to frameworks for temporal knowledge representation and reasoning, as well as temporal data mining and pattern discovery. Also discussed are the design principles of event mining systems. The approach is reified by the presentation of an event mining system called EventMiner, a computational framework for building explanatory models. The book contains case studies of using EventMiner in asthma risk management and an architecture for the objective self. The text can be used by researchers interested in harnessing the value of heterogeneous big data for designing explanatory event-based models in diverse application areas such as healthcare, biological data analytics, predictive maintenance of systems, computer networks, and business intelligence.
Author: Laleh Jalali
Publisher: Morgan & Claypool
ISBN: 1450384854
Category : Computers
Languages : en
Pages : 162
Get Book Here
Book Description
This book introduces the concept of Event Mining for building explanatory models from analyses of correlated data. Such a model may be used as the basis for predictions and corrective actions. The idea is to create, via an iterative process, a model that explains causal relationships in the form of structural and temporal patterns in the data. The first phase is the data-driven process of hypothesis formation, requiring the analysis of large amounts of data to find strong candidate hypotheses. The second phase is hypothesis testing, wherein a domain expert’s knowledge and judgment is used to test and modify the candidate hypotheses. The book is intended as a primer on Event Mining for data-enthusiasts and information professionals interested in employing these event-based data analysis techniques in diverse applications. The reader is introduced to frameworks for temporal knowledge representation and reasoning, as well as temporal data mining and pattern discovery. Also discussed are the design principles of event mining systems. The approach is reified by the presentation of an event mining system called EventMiner, a computational framework for building explanatory models. The book contains case studies of using EventMiner in asthma risk management and an architecture for the objective self. The text can be used by researchers interested in harnessing the value of heterogeneous big data for designing explanatory event-based models in diverse application areas such as healthcare, biological data analytics, predictive maintenance of systems, computer networks, and business intelligence.
Author: Laleh Jalali
Publisher: ACM Books
ISBN: 9781450384834
Category : Computers
Languages : en
Pages : 162
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Book Description
This book introduces the concept of Event Mining for building explanatory models from analyses of correlated data. Such a model may be used as the basis for predictions and corrective actions. The idea is to create, via an iterative process, a model that explains causal relationships in the form of structural and temporal patterns in the data. The first phase is the data-driven process of hypothesis formation, requiring the analysis of large amounts of data to find strong candidate hypotheses. The second phase is hypothesis testing, wherein a domain expert's knowledge and judgment is used to test and modify the candidate hypotheses. The book is intended as a primer on Event Mining for data-enthusiasts and information professionals interested in employing these event-based data analysis techniques in diverse applications. The reader is introduced to frameworks for temporal knowledge representation and reasoning, as well as temporal data mining and pattern discovery. Also discussed are the design principles of event mining systems. The approach is reified by the presentation of an event mining system called EventMiner, a computational framework for building explanatory models. The book contains case studies of using EventMiner in asthma risk management and an architecture for the objective self. The text can be used by researchers interested in harnessing the value of heterogeneous big data for designing explanatory event-based models in diverse application areas such as healthcare, biological data analytics, predictive maintenance of systems, computer networks, and business intelligence.
Author: Sumeet Dua
Publisher: CRC Press
ISBN: 1439839433
Category : Computers
Languages : en
Pages : 248
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Book Description
With the rapid advancement of information discovery techniques, machine learning and data mining continue to play a significant role in cybersecurity. Although several conferences, workshops, and journals focus on the fragmented research topics in this area, there has been no single interdisciplinary resource on past and current works and possible
Author: Meinel, Christoph
Publisher: Universitätsverlag Potsdam
ISBN: 3869563451
Category : Computers
Languages : en
Pages : 266
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Book Description
Design and implementation of service-oriented architectures impose numerous research questions from the fields of software engineering, system analysis and modeling, adaptability, and application integration. Service-oriented Systems Engineering represents a symbiosis of best practices in object orientation, component-based development, distributed computing, and business process management. It provides integration of business and IT concerns. Service-oriented Systems Engineering denotes a current research topic in the field of IT-Systems Engineering with high potential in academic research and industrial application. The annual Ph.D. Retreat of the Research School provides all members the opportunity to present the current state of their research and to give an outline of prospective Ph.D. projects. Due to the interdisciplinary structure of the Research School, this technical report covers a wide range of research topics. These include but are not limited to: Human Computer Interaction and Computer Vision as Service; Service-oriented Geovisualization Systems; Algorithm Engineering for Service-oriented Systems; Modeling and Verification of Self-adaptive Service-oriented Systems; Tools and Methods for Software Engineering in Service-oriented Systems; Security Engineering of Service-based IT Systems; Service-oriented Information Systems; Evolutionary Transition of Enterprise Applications to Service Orientation; Operating System Abstractions for Service-oriented Computing; and Services Specification, Composition, and Enactment.
Author: Emilio Porcu
Publisher: Springer Science & Business Media
ISBN: 3642170854
Category : Mathematics
Languages : en
Pages : 263
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Book Description
This book arises from the International Spring School "Advances and Challenges in Space-Time modelling of Natural Events," which took place March 2010. It details recent developments, new methods and applications in spatial statistics and related areas. This book arises from the International Spring School "Advances and Challenges in Space-Time modelling of Natural Events," which took place March 2010. It details recent developments, new methods and applications in spatial statistics and related areas.
Author: Kasiviswanathan KS
Publisher: Elsevier
ISBN: 0443186413
Category : Science
Languages : en
Pages : 342
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Book Description
Modeling and Mitigation Measures for Managing Extreme Hydrometeorological Events Under a Warming Climate explores the most recent computational tools, modeling frameworks, and critical data analysis measures for managing extreme climate events. Extreme climate events—primarily floods and droughts—have had major consequences in terms of loss of life and property around the world. Managing extreme occurrences, reducing their effects, and establishing adaptation strategies requires significant policy and planning improvements. This practical guide explores the latest research literature, recent advanced modeling approaches, and fundamental ideas and concepts to provide a variety of solutions for managing extreme events. - Discusses the impacts of climate change on the management of water resources - Provides flood and drought adaptation measures and strategies - Covers the latest research carried out in the modeling of extreme hydrometeorological variables
Author: Jose Julio Alferes
Publisher: Springer
ISBN: 3319420194
Category : Computers
Languages : en
Pages : 362
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Book Description
This book constitutes the refereed proceedings of the 10th International RuleML Symposium, RuleML 2016, held in New York, NY, USA during July 2016. The 19 full papers, 1 short paper, 2 keynote abstracts, 2 invited tutorial papers, 1 invited standard paper, presented were carefully reviewed and selected from 36 submissions. RuleML is a leading conference aiming to build bridges between academia and industry in the field of rules and its applications, especially as part of the semantic technology stack. It is devoted to rule-based programming and rule-based systems including production rule systems, logic programming rule engines, and business rule engines and business rule management systems, Semantic Web rule languages and rule standards and technologies, and research on inference rules, transformation rules, decision rules, and ECA rules.
Author: Daniel T. Larose
Publisher: John Wiley & Sons
ISBN: 0471756474
Category : Computers
Languages : en
Pages : 340
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Book Description
Apply powerful Data Mining Methods and Models to Leverage your Data for Actionable Results Data Mining Methods and Models provides: * The latest techniques for uncovering hidden nuggets of information * The insight into how the data mining algorithms actually work * The hands-on experience of performing data mining on large data sets Data Mining Methods and Models: * Applies a "white box" methodology, emphasizing an understanding of the model structures underlying the softwareWalks the reader through the various algorithms and provides examples of the operation of the algorithms on actual large data sets, including a detailed case study, "Modeling Response to Direct-Mail Marketing" * Tests the reader's level of understanding of the concepts and methodologies, with over 110 chapter exercises * Demonstrates the Clementine data mining software suite, WEKA open source data mining software, SPSS statistical software, and Minitab statistical software * Includes a companion Web site, www.dataminingconsultant.com, where the data sets used in the book may be downloaded, along with a comprehensive set of data mining resources. Faculty adopters of the book have access to an array of helpful resources, including solutions to all exercises, a PowerPoint(r) presentation of each chapter, sample data mining course projects and accompanying data sets, and multiple-choice chapter quizzes. With its emphasis on learning by doing, this is an excellent textbook for students in business, computer science, and statistics, as well as a problem-solving reference for data analysts and professionals in the field. An Instructor's Manual presenting detailed solutions to all the problems in the book is available onlne.
Author: Yanchang Zhao
Publisher: Academic Press
ISBN: 0124115209
Category : Computers
Languages : en
Pages : 493
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Book Description
Data Mining Applications with R is a great resource for researchers and professionals to understand the wide use of R, a free software environment for statistical computing and graphics, in solving different problems in industry. R is widely used in leveraging data mining techniques across many different industries, including government, finance, insurance, medicine, scientific research and more. This book presents 15 different real-world case studies illustrating various techniques in rapidly growing areas. It is an ideal companion for data mining researchers in academia and industry looking for ways to turn this versatile software into a powerful analytic tool. R code, Data and color figures for the book are provided at the RDataMining.com website. - Helps data miners to learn to use R in their specific area of work and see how R can apply in different industries - Presents various case studies in real-world applications, which will help readers to apply the techniques in their work - Provides code examples and sample data for readers to easily learn the techniques by running the code by themselves
Author: Wenzhong Shi
Publisher: Springer Nature
ISBN: 9811589836
Category : Social Science
Languages : en
Pages : 941
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Book Description
This open access book is the first to systematically introduce the principles of urban informatics and its application to every aspect of the city that involves its functioning, control, management, and future planning. It introduces new models and tools being developed to understand and implement these technologies that enable cities to function more efficiently – to become ‘smart’ and ‘sustainable’. The smart city has quickly emerged as computers have become ever smaller to the point where they can be embedded into the very fabric of the city, as well as being central to new ways in which the population can communicate and act. When cities are wired in this way, they have the potential to become sentient and responsive, generating massive streams of ‘big’ data in real time as well as providing immense opportunities for extracting new forms of urban data through crowdsourcing. This book offers a comprehensive review of the methods that form the core of urban informatics from various kinds of urban remote sensing to new approaches to machine learning and statistical modelling. It provides a detailed technical introduction to the wide array of tools information scientists need to develop the key urban analytics that are fundamental to learning about the smart city, and it outlines ways in which these tools can be used to inform design and policy so that cities can become more efficient with a greater concern for environment and equity.
