Download or read book Quality Measures in Data Mining written by Fabrice Guillet and published by Springer. This book was released on 2007-01-17 with total page 319 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents recent advances in quality measures in data mining.
Download or read book Quality Measures in Data Mining written by Fabrice Guillet and published by Springer Science & Business Media. This book was released on 2007-01-08 with total page 319 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents recent advances in quality measures in data mining.
Download or read book Uncertainty Handling and Quality Assessment in Data Mining written by Michalis Vazirgiannis and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 231 pages. Available in PDF, EPUB and Kindle. Book excerpt: The recent explosive growth of our ability to generate and store data has created a need for new, scalable and efficient, tools for data analysis. The main focus of the discipline of knowledge discovery in databases is to address this need. Knowledge discovery in databases is the fusion of many areas that are concerned with different aspects of data handling and data analysis, including databases, machine learning, statistics, and algorithms. Each of these areas addresses a different part of the problem, and places different emphasis on different requirements. For example, database techniques are designed to efficiently handle relatively simple queries on large amounts of data stored in external (disk) storage. Machine learning techniques typically consider smaller data sets, and the emphasis is on the accuracy ofa relatively complicated analysis task such as classification. The analysis of large data sets requires the design of new tools that not only combine and generalize techniques from different areas, but also require the design and development ofaltogether new scalable techniques.
Download or read book The Practitioner s Guide to Data Quality Improvement written by David Loshin and published by Elsevier. This book was released on 2010-11-22 with total page 432 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Practitioner's Guide to Data Quality Improvement offers a comprehensive look at data quality for business and IT, encompassing people, process, and technology. It shares the fundamentals for understanding the impacts of poor data quality, and guides practitioners and managers alike in socializing, gaining sponsorship for, planning, and establishing a data quality program. It demonstrates how to institute and run a data quality program, from first thoughts and justifications to maintenance and ongoing metrics. It includes an in-depth look at the use of data quality tools, including business case templates, and tools for analysis, reporting, and strategic planning. This book is recommended for data management practitioners, including database analysts, information analysts, data administrators, data architects, enterprise architects, data warehouse engineers, and systems analysts, and their managers. Offers a comprehensive look at data quality for business and IT, encompassing people, process, and technology. Shows how to institute and run a data quality program, from first thoughts and justifications to maintenance and ongoing metrics. Includes an in-depth look at the use of data quality tools, including business case templates, and tools for analysis, reporting, and strategic planning.
Download or read book Quality Aspects in Spatial Data Mining written by Alfred Stein and published by CRC Press. This book was released on 2016-04-19 with total page 378 pages. Available in PDF, EPUB and Kindle. Book excerpt: Describes the State-of-the-Art in Spatial Data Mining, Focuses on Data QualitySubstantial progress has been made toward developing effective techniques for spatial information processing in recent years. This science deals with models of reality in a GIS, however, and not with reality itself. Therefore, spatial information processes are often impre
Download or read book Integration Challenges for Analytics Business Intelligence and Data Mining written by Azevedo, Ana and published by IGI Global. This book was released on 2020-12-11 with total page 250 pages. Available in PDF, EPUB and Kindle. Book excerpt: As technology continues to advance, it is critical for businesses to implement systems that can support the transformation of data into information that is crucial for the success of the company. Without the integration of data (both structured and unstructured) mining in business intelligence systems, invaluable knowledge is lost. However, there are currently many different models and approaches that must be explored to determine the best method of integration. Integration Challenges for Analytics, Business Intelligence, and Data Mining is a relevant academic book that provides empirical research findings on increasing the understanding of using data mining in the context of business intelligence and analytics systems. Covering topics that include big data, artificial intelligence, and decision making, this book is an ideal reference source for professionals working in the areas of data mining, business intelligence, and analytics; data scientists; IT specialists; managers; researchers; academicians; practitioners; and graduate students.
Download or read book Knowledge Discovery and Data Mining Challenges and Realities written by Zhu, Xingquan and published by IGI Global. This book was released on 2007-04-30 with total page 290 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book provides a focal point for research and real-world data mining practitioners that advance knowledge discovery from low-quality data; it presents in-depth experiences and methodologies, providing theoretical and empirical guidance to users who have suffered from underlying low-quality data. Contributions also focus on interdisciplinary collaborations among data quality, data processing, data mining, data privacy, and data sharing"--Provided by publisher.
Download or read book Advances in Knowledge Discovery and Management written by Fabrice Guillet and published by Springer. This book was released on 2016-11-03 with total page 278 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a collection of representative and novel work in the field of data mining, knowledge discovery, clustering and classification, based on expanded and reworked versions of a selection of the best papers originally presented in French at the EGC 2014 and EGC 2015 conferences held in Rennes (France) in January 2014 and Luxembourg in January 2015. The book is in three parts: The first four chapters discuss optimization considerations in data mining. The second part explores specific quality measures, dissimilarities and ultrametrics. The final chapters focus on semantics, ontologies and social networks. Written for PhD and MSc students, as well as researchers working in the field, it addresses both theoretical and practical aspects of knowledge discovery and management.
Download or read book Trends and Applications in Knowledge Discovery and Data Mining written by Xiao-Li Li and published by Springer. This book was released on 2015-11-25 with total page 289 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings at PAKDD Workshops 2015, held in conjunction with PAKDD, the 19th Pacific-Asia Conference on Knowledge Discovery and Data Mining in Ho Chi Minh City, Vietnam, in May 2015. The 23 revised papers presented were carefully reviewed and selected from 57 submissions. The workshops affiliated with PAKDD 2015 include: Pattern Mining and Application of Big Data (BigPMA), Quality Issues, Measures of Interestingness and Evaluation of data mining models (QIMIE), Data Analytics for Evidence-based Healthcare (DAEBH), Vietnamese Language and Speech Processing (VLSP).
Download or read book Trends and Applications in Knowledge Discovery and Data Mining written by Jiuyong Li and published by Springer. This book was released on 2013-08-23 with total page 571 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings at PAKDD Workshops 2013, affiliated with the 17th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD) held in Gold Coast, Australia in April 2013. The 47 revised full papers presented were carefully reviewed and selected from 92 submissions. The workshops affiliated with PAKDD 2013 include: Data Mining Applications in Industry and Government (DMApps), Data Analytics for Targeted Healthcare (DANTH), Quality Issues, Measures of Interestingness and Evaluation of Data Mining Models (QIMIE), Biologically Inspired Techniques for Data Mining (BDM), Constraint Discovery and Application (CDA), Cloud Service Discovery (CloudSD).
Download or read book Data Preparation for Data Mining written by Dorian Pyle and published by Morgan Kaufmann. This book was released on 1999-03-22 with total page 566 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on the importance of clean, well-structured data as the first step to successful data mining. It shows how data should be prepared prior to mining in order to maximize mining performance.
Download or read book Recent Advances in Data Mining of Enterprise Data written by Thunshun Warren Liao and published by World Scientific. This book was released on 2008 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 ?enterprise data?. 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.
Download or read book Data Mining and Knowledge Discovery in Real Life Applications written by Julio Ponce and published by BoD – Books on Demand. This book was released on 2009-01-01 with total page 404 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents four different ways of theoretical and practical advances and applications of data mining in different promising areas like Industrialist, Biological, and Social. Twenty six chapters cover different special topics with proposed novel ideas. Each chapter gives an overview of the subjects and some of the chapters have cases with offered data mining solutions. We hope that this book will be a useful aid in showing a right way for the students, researchers and practitioners in their studies.
Download or read book Integration of Data Mining in Business Intelligence Systems written by Azevedo, Ana and published by IGI Global. This book was released on 2014-09-30 with total page 340 pages. Available in PDF, EPUB and Kindle. Book excerpt: Uncovering and analyzing data associated with the current business environment is essential in maintaining a competitive edge. As such, making informed decisions based on this data is crucial to managers across industries. Integration of Data Mining in Business Intelligence Systems investigates the incorporation of data mining into business technologies used in the decision making process. Emphasizing cutting-edge research and relevant concepts in data discovery and analysis, this book is a comprehensive reference source for policymakers, academicians, researchers, students, technology developers, and professionals interested in the application of data mining techniques and practices in business information systems.
Download or read book Protecting Individual Privacy in the Struggle Against Terrorists written by National Research Council and published by National Academies Press. This book was released on 2008-10-26 with total page 377 pages. Available in PDF, EPUB and Kindle. Book excerpt: All U.S. agencies with counterterrorism programs that collect or "mine" personal data-such as phone records or Web sites visited-should be required to evaluate the programs' effectiveness, lawfulness, and impacts on privacy. A framework is offered that agencies can use to evaluate such information-based programs, both classified and unclassified. The book urges Congress to re-examine existing privacy law to assess how privacy can be protected in current and future programs and recommends that any individuals harmed by violations of privacy be given a meaningful form of redress. Two specific technologies are examined: data mining and behavioral surveillance. Regarding data mining, the book concludes that although these methods have been useful in the private sector for spotting consumer fraud, they are less helpful for counterterrorism because so little is known about what patterns indicate terrorist activity. Regarding behavioral surveillance in a counterterrorist context, the book concludes that although research and development on certain aspects of this topic are warranted, there is no scientific consensus on whether these techniques are ready for operational use at all in counterterrorism.
Download or read book New Frontiers in Applied Data Mining written by Longbing Cao and published by Springer. This book was released on 2012-02-21 with total page 526 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly refereed post-conference proceedings of five international workshops held in conjunction with PAKDD 2011 in Shenzhen, China, in May 2011: the International Workshop on Behavior Informatics (BI 2011), the Workshop on Quality Issues, Measures of Interestingness and Evaluation of Data Mining Models (QIMIE 2011), the Workshop on Biologically Inspired Techniques for Data Mining (BDM 2011), the Workshop on Advances and Issues in Traditional Chinese Medicine Clinical Data Mining (AI-TCM 2011), and the Second Workshop on Data Mining for Healthcare Management (DMGHM 2011). The book also includes papers from the First PAKDD Doctoral Symposium on Data Mining (DSDM 2011). The 42 papers were carefully reviewed and selected from numerous submissions. The papers cover a wide range of topics discussing emerging techniques in the field of knowledge discovery in databases and their application domains extending to previously unexplored areas such as data mining based on optimization techniques from biological behavior of animals and applications in Traditional Chinese Medicine clinical research and health care management.
Download or read book Data Mining written by Jiawei Han and published by Morgan Kaufmann. This book was released on 2022-07-02 with total page 786 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Mining: Concepts and Techniques, Fourth Edition introduces concepts, principles, and methods for mining patterns, knowledge, and models from various kinds of data for diverse applications. Specifically, it delves into the processes for uncovering patterns and knowledge from massive collections of data, known as knowledge discovery from data, or KDD. It focuses on the feasibility, usefulness, effectiveness, and scalability of data mining techniques for large data sets. After an introduction to the concept of data mining, the authors explain the methods for preprocessing, characterizing, and warehousing data. They then partition the data mining methods into several major tasks, introducing concepts and methods for mining frequent patterns, associations, and correlations for large data sets; data classificcation and model construction; cluster analysis; and outlier detection. Concepts and methods for deep learning are systematically introduced as one chapter. Finally, the book covers the trends, applications, and research frontiers in data mining. Presents a comprehensive new chapter on deep learning, including improving training of deep learning models, convolutional neural networks, recurrent neural networks, and graph neural networks Addresses advanced topics in one dedicated chapter: data mining trends and research frontiers, including mining rich data types (text, spatiotemporal data, and graph/networks), data mining applications (such as sentiment analysis, truth discovery, and information propagattion), data mining methodologie and systems, and data mining and society Provides a comprehensive, practical look at the concepts and techniques needed to get the most out of your data
