Download or read book Hierarchical Aggregation of Multidimensional Data for Efficient Data Mining written by Safaa Khalil Alwajidi and published by . This book was released on 2020 with total page 114 pages. Available in PDF, EPUB and Kindle. Book excerpt: Big data analysis is essential for many smart applications in areas such as connected healthcare, intelligent transportation, human activity recognition, environment, and climate change monitoring. Traditional data mining algorithms do not scale well to big data due to the enormous number of data points and the velocity of their generation. Mining and learning from big data need time and memory efficiency techniques, albeit the cost of possible loss in accuracy. This research focuses on the mining of big data using aggregated data as input. We developed a data structure that is to be used to aggregate data at multiple resolutions. The structure is built once, updated incrementally, and serves as data input for data mining algorithms instead of accessing the raw data. We adapted several existing data mining algorithms and developed new algorithms to accept multiresolution aggregated data instead of raw data as input. Example data mining algorithms include Bayes classifiers, entropy discretization, decision trees, and support vector machines. We studied visual analytics of high dimensional big data by visually exploring the multiresolution data aggregation structure. We have developed techniques for pruning and visualizing data cube lattices. Learning from multiple levels of data aggregation enables users to compromise between time, memory, and accuracy, depending on available resources and application requirements. The multiresolution aggregation gives opportunities to develop new data mining methods and algorithms.
Download or read book Data Warehousing and Mining written by ITLESL and published by Pearson Education India. This book was released on 2012 with total page 271 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Warehousing and Data Mining is presented in a question-and-answer format following the examination pattern and covers all key topics in the syllabus. The book is designed to make learning fast and effective and is precise, up-to-date and will help students excel in their examinations. The book is part of the Express Learning is a series of books designed as quick reference guides to important undergraduate courses. The organized and accessible format of these books allows students to learn important concepts in an easy-to-understand, question-and-answer format. These portable learning tools have been designed as one-stop references for students to understand and master the subjects by themselves.
Download or read book Dynamic Cubing for Hierarchical Multidimensional Data Space written by Usman Ahmed and published by . This book was released on 2013 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data warehouses are being used in many applications since quite a long time. Traditionally, new data in these warehouses is loaded through offline bulk updates which implies that latest data is not always available for analysis. This, however, is not acceptable in many modern applications (such as intelligent building, smart grid etc.) that require the latest data for decision making. These modern applications necessitate real-time fast atomic integration of incoming facts in data warehouse. Moreover, the data defining the analysis dimensions, stored in dimension tables of these warehouses, also needs to be updated in real-time, in case of any change. In this thesis, such real-time data warehouses are defined as dynamic data warehouses. We propose a data model for these dynamic data warehouses and present the concept of Hierarchical Hybrid Multidimensional Data Space (HHMDS) which constitutes of both ordered and non-ordered hierarchical dimensions. The axes of the data space are non-ordered which help their dynamic evolution without any need of reordering. We define a data grouping structure, called Minimum Bounding Space (MBS), that helps efficient data partitioning of data in the space. Various operators, relations and metrics are defined which are used for the optimization of these data partitions and the analogies among classical OLAP concepts and the HHMDS are defined. We propose efficient algorithms to store summarized or detailed data, in form of MBS, in a tree structure called DyTree. Algorithms for OLAP queries over the DyTree are also detailed. The nodes of DyTree, holding MBS with associated aggregated measure values, represent materialized sections of cuboids and tree as a whole is a partially materialized and indexed data cube which is maintained using online atomic incremental updates. We propose a methodology to experimentally evaluate partial data cubing techniques and a prototype implementing this methodology is developed. The prototype lets us experimentally evaluate and simulate the structure and performance of the DyTree against other solutions. An extensive study is conducted using this prototype which shows that the DyTree is an efficient and effective partial data cubing solution for a dynamic data warehousing environment.
Download or read book The Handbook of Data Mining written by Nong Ye and published by CRC Press. This book was released on 2003-04-01 with total page 720 pages. Available in PDF, EPUB and Kindle. Book excerpt: Created with the input of a distinguished International Board of the foremost authorities in data mining from academia and industry, The Handbook of Data Mining presents comprehensive coverage of data mining concepts and techniques. Algorithms, methodologies, management issues, and tools are all illustrated through engaging examples and real-world applications to ease understanding of the materials. This book is organized into three parts. Part I presents various data mining methodologies, concepts, and available software tools for each methodology. Part II addresses various issues typically faced in the management of data mining projects and tips on how to maximize outcome utility. Part III features numerous real-world applications of these techniques in a variety of areas, including human performance, geospatial, bioinformatics, on- and off-line customer transaction activity, security-related computer audits, network traffic, text and image, and manufacturing quality. This Handbook is ideal for researchers and developers who want to use data mining techniques to derive scientific inferences where extensive data is available in scattered reports and publications. It is also an excellent resource for graduate-level courses on data mining and decision and expert systems methodology.
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.
Download or read book Intelligent Data Warehousing written by Zhengxin Chen and published by CRC Press. This book was released on 2001-12-13 with total page 259 pages. Available in PDF, EPUB and Kindle. Book excerpt: Effective decision support systems (DSS) are quickly becoming key to businesses gaining a competitive advantage, and the effectiveness of these systems depends on the ability to construct, maintain, and extract information from data warehouses. While many still perceive data warehousing as a subdiscipline of management information systems (MIS), in
Download or read book New Trends in Data Warehousing and Data Analysis written by Stanislaw Kozielski and published by Springer Science & Business Media. This book was released on 2008-10-23 with total page 355 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.
Download or read book Grouping Multidimensional Data written by Jacob Kogan and published by Springer Science & Business Media. This book was released on 2006-02-08 with total page 273 pages. Available in PDF, EPUB and Kindle. Book excerpt: Clustering is one of the most fundamental and essential data analysis techniques. Clustering can be used as an independent data mining task to discern intrinsic characteristics of data, or as a preprocessing step with the clustering results then used for classification, correlation analysis, or anomaly detection. Kogan and his co-editors have put together recent advances in clustering large and high-dimension data. Their volume addresses new topics and methods which are central to modern data analysis, with particular emphasis on linear algebra tools, opimization methods and statistical techniques. The contributions, written by leading researchers from both academia and industry, cover theoretical basics as well as application and evaluation of algorithms, and thus provide an excellent state-of-the-art overview. The level of detail, the breadth of coverage, and the comprehensive bibliography make this book a perfect fit for researchers and graduate students in data mining and in many other important related application areas.
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 - Visit the author-hosted companion site, https://hanj.cs.illinois.edu/bk4/ for downloadable lecture slides and errata
Download or read book Data Mining Warehousing written by Ikvinderpal Singh and published by KHANNA PUBLISHING HOUSE. This book was released on 2014 with total page 342 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book has numerous features that make it a winner, The order of topics is very logical, The choice of topics is quite appropriate for a comprehensive introductory book. The subject matter is logically structured, with chapters covering essential components of the data mining and warehousing field. The sequence of topics is well planned to provide a seamless transition from design to implementation. Within each chapter, the continuity of topics is excellent. The figures appropriately enhance and amplify the topics. The exercises can be found at the end of each chapter.
Download or read book Data Warehouse and Data Mining written by Dr. Jugnesh Kumar and published by BPB Publications. This book was released on 2024-01-25 with total page 261 pages. Available in PDF, EPUB and Kindle. Book excerpt: Unveiling insights, unleashing potential: Navigating the depths of data warehousing and mining for a data-driven tomorrow KEY FEATURES ● Explore concepts ranging from fundamentals to advanced techniques of data warehouses and data mining. ● Translate business questions into actionable strategies to make informed decisions. ● Gain practical implementation guidance for hands-on learning. DESCRIPTION Data warehouse and data mining are essential technologies in the field of data analysis and business intelligence. Data warehouse provides a centralized repository of structured data and facilitates data storage and retrieval. Data mining, on the other hand, utilizes various algorithms and techniques to extract valuable patterns, trends, and insights from large datasets. The book explains the ins and outs of data warehousing by discussing its principles, benefits, and components, differentiating it from traditional databases. The readers will explore warehouse architecture, learn to navigate OLTP and OLAP systems, grasping the crux of the difference between ROLAP and MOLAP. The book is designed to help you discover data mining secrets with techniques like classification and clustering. You will be able to advance your skills by handling multimedia, time series, and text, staying ahead in the evolving data mining landscape. By the end of this book, you will be equipped with the skills and knowledge to confidently translate business questions into actionable strategies, extracting valuable insights for informed decisions. WHAT YOU WILL LEARN ● Designing and building efficient data warehouses. ● Handling diverse data types for comprehensive insights. ● Mastering various data mining techniques. ● Translating business questions into mining strategies. ● Techniques for pattern discovery and knowledge extraction. WHO THIS BOOK IS FOR From aspiring data analysts, data professionals, IT managers, to business intelligence practitioners, this book caters to a diverse audience. TABLE OF CONTENTS 1. Introduction to Data Warehousing 2. Data Warehouse Process and Architecture 3. Data Warehouse Implementation 4. Data Mining Definition and Task 5. Data Mining Query Languages 6. Data Mining Techniques 7. Mining Complex Data Objects
Download or read book Relational Data Mining written by Saso Dzeroski and published by Springer Science & Business Media. This book was released on 2013-04-17 with total page 410 pages. Available in PDF, EPUB and Kindle. Book excerpt: As the first book devoted to relational data mining, this coherently written multi-author monograph provides a thorough introduction and systematic overview of the area. The first part introduces the reader to the basics and principles of classical knowledge discovery in databases and inductive logic programming; subsequent chapters by leading experts assess the techniques in relational data mining in a principled and comprehensive way; finally, three chapters deal with advanced applications in various fields and refer the reader to resources for relational data mining. This book will become a valuable source of reference for R&D professionals active in relational data mining. Students as well as IT professionals and ambitioned practitioners interested in learning about relational data mining will appreciate the book as a useful text and gentle introduction to this exciting new field.
Download or read book Hierarchical Aggregate Structure by Inductive Aggregation for Interactive Data Visualization written by Nasim Razavi and published by . This book was released on 2016 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data visualization is a method to facilitate the process of knowledge discovery and decision making. Effective and practical visual analytic systems have to support real-time and smooth interaction. Traditional data processing techniques and systems are inadequate when it comes to large datasets. The powerful features of relational database engines can be adapted to facilitate the visual representation of very large datasets. In this thesis, we propose techniques to provide a tightly coupled system with a database engine back-end to support a data visualization front-end. We employ data reduction techniques along with other methods to form a hierarchical data structure that we call the inductive-aggregate pyramid to provide multiple representations of data. We also propose a generalized form of inductive-aggregate pyramids that we call cubed pyramids to provide a richer representation of high-dimensional data. We develop and employ techniques to build and query efficiently these structures to support interactive data visualization.
Download or read book Data Mining written by Krzysztof J. Cios and published by Springer Science & Business Media. This book was released on 2007-10-05 with total page 601 pages. Available in PDF, EPUB and Kindle. Book excerpt: This comprehensive textbook on data mining details the unique steps of the knowledge discovery process that prescribes the sequence in which data mining projects should be performed, from problem and data understanding through data preprocessing to deployment of the results. This knowledge discovery approach is what distinguishes Data Mining from other texts in this area. The book provides a suite of exercises and includes links to instructional presentations. Furthermore, it contains appendices of relevant mathematical material.
Download or read book Data Mining and Knowledge Discovery Technologies written by Taniar, David and published by IGI Global. This book was released on 2008-01-31 with total page 380 pages. Available in PDF, EPUB and Kindle. Book excerpt: As information technology continues to advance in massive increments, the bank of information available from personal, financial, and business electronic transactions and all other electronic documentation and data storage is growing at an exponential rate. With this wealth of information comes the opportunity and necessity to utilize this information to maintain competitive advantage and process information effectively in real-world situations. Data Mining and Knowledge Discovery Technologies presents researchers and practitioners in fields such as knowledge management, information science, Web engineering, and medical informatics, with comprehensive, innovative research on data mining methods, structures, tools, and methods, the knowledge discovery process, and data marts, among many other cutting-edge topics.
Download or read book New Fundamental Technologies in Data Mining written by Kimito Funatsu and published by BoD – Books on Demand. This book was released on 2011-01-21 with total page 600 pages. Available in PDF, EPUB and Kindle. Book excerpt: The progress of data mining technology and large public popularity establish a need for a comprehensive text on the subject. The series of books entitled by "Data Mining" address the need by presenting in-depth description of novel mining algorithms and many useful applications. In addition to understanding each section deeply, the two books present useful hints and strategies to solving problems in the following chapters. The contributing authors have highlighted many future research directions that will foster multi-disciplinary collaborations and hence will lead to significant development in the field of data mining.
Download or read book Complex Data Warehousing and Knowledge Discovery for Advanced Retrieval Development Innovative Methods and Applications written by Nguyen, Tho Manh and published by IGI Global. This book was released on 2009-07-31 with total page 426 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recently, researchers have focused on challenging problems facing the development of data warehousing, knowledge discovery, and data mining applications.
