Recent Advances In Data Mining Of Enterprise Data

Author : T. Warren Liao
Publisher : World Scientific
ISBN 13 : 9812779868
Total Pages : 816 pages
Book Rating : 4.61/5 ( download)

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Download or read book Recent Advances in Data Mining of Enterprise Data written by T. Warren Liao and published by World Scientific. This book was released on 2008-01-15 with total page 816 pages. Available in PDF, EPUB and Kindle. Book excerpt: The main goal of the new field of data mining is the analysis of large and complex datasets. Some very important datasets may be derived from business and industrial activities. This kind of data is known as OC enterprise dataOCO. The common characteristic of such datasets is that the analyst wishes to analyze them for the purpose of designing a more cost-effective strategy for optimizing some type of performance measure, such as reducing production time, improving quality, eliminating wastes, or maximizing profit. Data in this category may describe different scheduling scenarios in a manufacturing environment, quality control of some process, fault diagnosis in the operation of a machine or process, risk analysis when issuing credit to applicants, management of supply chains in a manufacturing system, or data for business related decision-making. Sample Chapter(s). Foreword (37 KB). Chapter 1: Enterprise Data Mining: A Review and Research Directions (655 KB). Contents: Enterprise Data Mining: A Review and Research Directions (T W Liao); Application and Comparison of Classification Techniques in Controlling Credit Risk (L Yu et al.); Predictive Classification with Imbalanced Enterprise Data (S Daskalaki et al.); Data Mining Applications of Process Platform Formation for High Variety Production (J Jiao & L Zhang); Multivariate Control Charts from a Data Mining Perspective (G C Porzio & G Ragozini); Maintenance Planning Using Enterprise Data Mining (L P Khoo et al.); Mining Images of Cell-Based Assays (P Perner); Support Vector Machines and Applications (T B Trafalis & O O Oladunni); A Survey of Manifold-Based Learning Methods (X Huo et al.); and other papers. Readership: Graduate students in engineering, computer science, and business schools; researchers and practioners of data mining with emphazis of enterprise data mining."

Author : Taniar, David
Publisher : IGI Global
ISBN 13 : 1613504756
Total Pages : 465 pages
Book Rating : 4.58/5 ( download)

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Download or read book Exploring Advances in Interdisciplinary Data Mining and Analytics: New Trends written by Taniar, David and published by IGI Global. This book was released on 2011-12-31 with total page 465 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book is an updated look at the state of technology in the field of data mining and analytics offering the latest technological, analytical, ethical, and commercial perspectives on topics in data mining"--Provided by publisher.

Author : Hamid R. Nemati
Publisher : IGI Global
ISBN 13 : 1591401356
Total Pages : 371 pages
Book Rating : 4.53/5 ( download)

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Download or read book Organizational Data Mining written by Hamid R. Nemati and published by IGI Global. This book was released on 2004-01-01 with total page 371 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mountains of business data are piling up in organizations every day. These organizations collect data from multiple sources, both internal and external. These sources include legacy systems, customer relationship management and enterprise resource planning applications, online and e-commerce systems, government organizations and business suppliers and partners. A recent study from the University of California at Berkeley found the amount of data organizations collect and store in enterprise databases doubles every year, and slightly more than half of this data will consist of "reference information," which is the kind of information strategic business applications and decision support systems demand (Kestelyn, 2002). Terabyte-sized (1,000 megabytes) databases are commonplace in organizations today, and this enormous growth will make petabyte-sized databases (1,000 terabytes) a reality within the next few years (Whiting, 2002). By 2004 the Gartner Group estimates worldwide data volumes will be 30 times those of 1999, which translates into more data having been produced in the last 30 years than during the previous 5,000 (Wurman, 1989).

Author : Neal Fishman
Publisher : John Wiley & Sons
ISBN 13 : 111969342X
Total Pages : 374 pages
Book Rating : 4.20/5 ( download)

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Download or read book Smarter Data Science written by Neal Fishman and published by John Wiley & Sons. This book was released on 2020-04-14 with total page 374 pages. Available in PDF, EPUB and Kindle. Book excerpt: Organizations can make data science a repeatable, predictable tool, which business professionals use to get more value from their data Enterprise data and AI projects are often scattershot, underbaked, siloed, and not adaptable to predictable business changes. As a result, the vast majority fail. These expensive quagmires can be avoided, and this book explains precisely how. Data science is emerging as a hands-on tool for not just data scientists, but business professionals as well. Managers, directors, IT leaders, and analysts must expand their use of data science capabilities for the organization to stay competitive. Smarter Data Science helps them achieve their enterprise-grade data projects and AI goals. It serves as a guide to building a robust and comprehensive information architecture program that enables sustainable and scalable AI deployments. When an organization manages its data effectively, its data science program becomes a fully scalable function that’s both prescriptive and repeatable. With an understanding of data science principles, practitioners are also empowered to lead their organizations in establishing and deploying viable AI. They employ the tools of machine learning, deep learning, and AI to extract greater value from data for the benefit of the enterprise. By following a ladder framework that promotes prescriptive capabilities, organizations can make data science accessible to a range of team members, democratizing data science throughout the organization. Companies that collect, organize, and analyze data can move forward to additional data science achievements: Improving time-to-value with infused AI models for common use cases Optimizing knowledge work and business processes Utilizing AI-based business intelligence and data visualization Establishing a data topology to support general or highly specialized needs Successfully completing AI projects in a predictable manner Coordinating the use of AI from any compute node. From inner edges to outer edges: cloud, fog, and mist computing When they climb the ladder presented in this book, businesspeople and data scientists alike will be able to improve and foster repeatable capabilities. They will have the knowledge to maximize their AI and data assets for the benefit of their organizations.

Author : Katja Windt
Publisher : Springer Science & Business Media
ISBN 13 : 3642307493
Total Pages : 553 pages
Book Rating : 4.92/5 ( download)

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Download or read book Robust Manufacturing Control written by Katja Windt and published by Springer Science & Business Media. This book was released on 2012-12-14 with total page 553 pages. Available in PDF, EPUB and Kindle. Book excerpt: This contributed volume collects research papers, presented at the CIRP Sponsored Conference Robust Manufacturing Control: Innovative and Interdisciplinary Approaches for Global Networks (RoMaC 2012, Jacobs University, Bremen, Germany, June 18th-20th 2012). These research papers present the latest developments and new ideas focusing on robust manufacturing control for global networks. Today, Global Production Networks (i.e. the nexus of interconnected material and information flows through which products and services are manufactured, assembled and distributed) are confronted with and expected to adapt to: sudden and unpredictable large-scale changes of important parameters which are occurring more and more frequently, event propagation in networks with high degree of interconnectivity which leads to unforeseen fluctuations, and non-equilibrium states which increasingly characterize daily business. These multi-scale changes deeply influence logistic target achievement and call for robust planning and control strategies. Therefore, understanding the cause and effects of multi-scale changes in production networks is of major interest. New methodological approaches from different science disciplines are promising to contribute to a new level comprehension of network processes. Unconventional methods from biology, perturbation ecology or auditory display are gaining increasing importance as they are confronted with similar challenges. Advancements from the classical disciplines such as mathematics, physics and engineering are also becoming of continuing importance.

Author : Stanisław Kozielski
Publisher : Springer Science & Business Media
ISBN 13 : 9780387874302
Total Pages : 365 pages
Book Rating : 4.05/5 ( download)

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Download or read book New Trends in Data Warehousing and Data Analysis written by Stanisław Kozielski and published by Springer Science & Business Media. This book was released on 2008-11-21 with total page 365 pages. Available in PDF, EPUB and Kindle. Book excerpt: Most of modern enterprises, institutions, and organizations rely on knowledge-based management systems. In these systems, knowledge is gained from data analysis. Today, knowledge-based management systems include data warehouses as their core components. Data integrated in a data warehouse are analyzed by the so-called On-Line Analytical Processing (OLAP) applications designed to discover trends, patterns of behavior, and anomalies as well as finding dependencies between data. Massive amounts of integrated data and the complexity of integrated data coming from many different sources make data integration and processing challenging. New Trends in Data Warehousing and Data Analysis brings together the most recent research and practical achievements in the DW and OLAP technologies. It provides an up-to-date bibliography of published works and the resource of research achievements. Finally, the book assists in the dissemination of knowledge in the field of advanced DW and OLAP.

Author : Atzmueller, Martin
Publisher : IGI Global
ISBN 13 : 1522502947
Total Pages : 272 pages
Book Rating : 4.44/5 ( download)

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Download or read book Enterprise Big Data Engineering, Analytics, and Management written by Atzmueller, Martin and published by IGI Global. This book was released on 2016-06-01 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt: The significance of big data can be observed in any decision-making process as it is often used for forecasting and predictive analytics. Additionally, big data can be used to build a holistic view of an enterprise through a collection and analysis of large data sets retrospectively. As the data deluge deepens, new methods for analyzing, comprehending, and making use of big data become necessary. Enterprise Big Data Engineering, Analytics, and Management presents novel methodologies and practical approaches to engineering, managing, and analyzing large-scale data sets with a focus on enterprise applications and implementation. Featuring essential big data concepts including data mining, artificial intelligence, and information extraction, this publication provides a platform for retargeting the current research available in the field. Data analysts, IT professionals, researchers, and graduate-level students will find the timely research presented in this publication essential to furthering their knowledge in the field.

Author : Longbing Cao
Publisher : Springer Science & Business Media
ISBN 13 : 0387794204
Total Pages : 310 pages
Book Rating : 4.04/5 ( download)

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Download or read book Data Mining for Business Applications written by Longbing Cao and published by Springer Science & Business Media. This book was released on 2008-10-03 with total page 310 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Mining for Business Applications presents the state-of-the-art research and development outcomes on methodologies, techniques, approaches and successful applications in the area. The contributions mark a paradigm shift from “data-centered pattern mining” to “domain driven actionable knowledge discovery” for next-generation KDD research and applications. The contents identify how KDD techniques can better contribute to critical domain problems in theory and practice, and strengthen business intelligence in complex enterprise applications. The volume also explores challenges and directions for future research and development in the dialogue between academia and business.

Author : Longbing Cao
Publisher : Springer Science & Business Media
ISBN 13 : 1441957375
Total Pages : 251 pages
Book Rating : 4.75/5 ( download)

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Download or read book Domain Driven Data Mining written by Longbing Cao and published by Springer Science & Business Media. This book was released on 2010-01-08 with total page 251 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers state-of the-art research and development outcomes on methodologies, techniques, approaches and successful applications in domain driven, actionable knowledge discovery. It bridges the gap between business expectations and research output.

Author : Trivedi, Shrawan Kumar
Publisher : IGI Global
ISBN 13 : 1522520325
Total Pages : 438 pages
Book Rating : 4.20/5 ( download)

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Download or read book Handbook of Research on Advanced Data Mining Techniques and Applications for Business Intelligence written by Trivedi, Shrawan Kumar and published by IGI Global. This book was released on 2017-02-14 with total page 438 pages. Available in PDF, EPUB and Kindle. Book excerpt: The development of business intelligence has enhanced the visualization of data to inform and facilitate business management and strategizing. By implementing effective data-driven techniques, this allows for advance reporting tools to cater to company-specific issues and challenges. The Handbook of Research on Advanced Data Mining Techniques and Applications for Business Intelligence is a key resource on the latest advancements in business applications and the use of mining software solutions to achieve optimal decision-making and risk management results. Highlighting innovative studies on data warehousing, business activity monitoring, and text mining, this publication is an ideal reference source for research scholars, management faculty, and practitioners.