Mining Of Data With Complex Structures
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| Author | : Fedja Hadzic |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 340 |
| Release | : 2011-01-30 |
| Genre | : Computers |
| ISBN | : 3642175562 |
Mining of Data with Complex Structures: - Clarifies the type and nature of data with complex structure including sequences, trees and graphs - Provides a detailed background of the state-of-the-art of sequence mining, tree mining and graph mining. - Defines the essential aspects of the tree mining problem: subtree types, support definitions, constraints. - Outlines the implementation issues one needs to consider when developing tree mining algorithms (enumeration strategies, data structures, etc.) - Details the Tree Model Guided (TMG) approach for tree mining and provides the mathematical model for the worst case estimate of complexity of mining ordered induced and embedded subtrees. - Explains the mechanism of the TMG framework for mining ordered/unordered induced/embedded and distance-constrained embedded subtrees. - Provides a detailed comparison of the different tree mining approaches highlighting the characteristics and benefits of each approach. - Overviews the implications and potential applications of tree mining in general knowledge management related tasks, and uses Web, health and bioinformatics related applications as case studies. - Details the extension of the TMG framework for sequence mining - Provides an overview of the future research direction with respect to technical extensions and application areas The primary audience is 3rd year, 4th year undergraduate students, Masters and PhD students and academics. The book can be used for both teaching and research. The secondary audiences are practitioners in industry, business, commerce, government and consortiums, alliances and partnerships to learn how to introduce and efficiently make use of the techniques for mining of data with complex structures into their applications. The scope of the book is both theoretical and practical and as such it will reach a broad market both within academia and industry. In addition, its subject matter is a rapidly emerging field that is critical for efficient analysis of knowledge stored in various domains.
| Author | : Zbigniew W. Ras |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 275 |
| Release | : 2008-05-26 |
| Genre | : Computers |
| ISBN | : 3540684158 |
This book constitutes the refereed proceedings of the Third International Workshop on Mining Complex Data, MCD 2007, held in Warsaw, Poland, in September 2007, co-located with ECML and PKDD 2007. The 20 revised full papers presented were carefully reviewed and selected; they present original results on knowledge discovery from complex data. In contrast to the typical tabular data, complex data can consist of heterogenous data types, can come from different sources, or live in high dimensional spaces. All these specificities call for new data mining strategies.
| Author | : Rokia Missaoui |
| Publisher | : Springer |
| Total Pages | : 0 |
| Release | : 2023-07-01 |
| Genre | : Computers |
| ISBN | : 9783030932800 |
FCA is an important formalism that is associated with a variety of research areas such as lattice theory, knowledge representation, data mining, machine learning, and semantic Web. It is successfully exploited in an increasing number of application domains such as software engineering, information retrieval, social network analysis, and bioinformatics. Its mathematical power comes from its concept lattice formalization in which each element in the lattice captures a formal concept while the whole structure represents a conceptual hierarchy that offers browsing, clustering and association rule mining. Complex data analytics refers to advanced methods and tools for mining and analyzing data with complex structures such as XML/Json data, text and image data, multidimensional data, graphs, sequences and streaming data. It also covers visualization mechanisms used to highlight the discovered knowledge. This edited book examines a set of important and relevant research directions in complex data management, and updates the contribution of the FCA community in analyzing complex and large data such as knowledge graphs and interlinked contexts. For example, Formal Concept Analysis and some of its extensions are exploited, revisited and coupled with recent processing parallel and distributed paradigms to maximize the benefits in analyzing large data.
| Author | : Jiawei Han |
| Publisher | : Elsevier |
| Total Pages | : 740 |
| Release | : 2011-06-09 |
| Genre | : Computers |
| ISBN | : 0123814804 |
Data Mining: Concepts and Techniques provides the concepts and techniques in processing gathered data or information, which will be used in various applications. Specifically, it explains data mining and the tools used in discovering knowledge from the collected data. This book is referred as the knowledge discovery from data (KDD). It focuses on the feasibility, usefulness, effectiveness, and scalability of techniques of large data sets. After describing data mining, this edition explains the methods of knowing, preprocessing, processing, and warehousing data. It then presents information about data warehouses, online analytical processing (OLAP), and data cube technology. Then, the methods involved in mining frequent patterns, associations, and correlations for large data sets are described. The book details the methods for data classification and introduces the concepts and methods for data clustering. The remaining chapters discuss the outlier detection and the trends, applications, and research frontiers in data mining. This book is intended for Computer Science students, application developers, business professionals, and researchers who seek information on data mining. - Presents dozens of algorithms and implementation examples, all in pseudo-code and suitable for use in real-world, large-scale data mining projects - Addresses advanced topics such as mining object-relational databases, spatial databases, multimedia databases, time-series databases, text databases, the World Wide Web, and applications in several fields - Provides a comprehensive, practical look at the concepts and techniques you need to get the most out of your data
| Author | : Jake Y. Chen |
| Publisher | : CRC Press |
| Total Pages | : 736 |
| Release | : 2009-09-01 |
| Genre | : Computers |
| ISBN | : 1420086855 |
Like a data-guzzling turbo engine, advanced data mining has been powering post-genome biological studies for two decades. Reflecting this growth, Biological Data Mining presents comprehensive data mining concepts, theories, and applications in current biological and medical research. Each chapter is written by a distinguished team of interdisciplin
| Author | : Jure Leskovec |
| Publisher | : Cambridge University Press |
| Total Pages | : 480 |
| Release | : 2014-11-13 |
| Genre | : Computers |
| ISBN | : 1107077230 |
Now in its second edition, this book focuses on practical algorithms for mining data from even the largest datasets.
| Author | : Debiao Meng |
| Publisher | : CRC Press |
| Total Pages | : 349 |
| Release | : 2024-09-02 |
| Genre | : Technology & Engineering |
| ISBN | : 1040113516 |
In the realm of engineering structures design, the inevitability of uncertainties poses a significant challenge. Uncertainty-Based Multidisciplinary Design and Optimization (UBMDO) stands out for its dual ability to precisely quantify the impact of uncertain variables and harness the potential of multidisciplinary design and optimization, thereby attracting considerable attention. From basic theory to advanced applications, this book helps readers achieve more efficient and reliable design optimization in complex systems through rich case studies and practical technical guidance. The book systematically expounds the fundamental theories and methods of UBMDO, encompassing crucial techniques such as uncertainty modeling, sensitivity analysis, approximate modeling, and uncertainty-based optimization. It also introduces various uncertainty analysis methods, such as stochastic, non-probabilistic, and hybrid approaches, aiding readers in comprehending and managing uncertainty within systems. Through diverse practical engineering cases in fields like machinery, aerospace, and energy, it illustrates the specific application and implementation process of the UBMDO method. Rich graphics, algorithms, and simulation results augment the practicality and applicability of the theoretical knowledge. Furthermore, it explores in depth the future development trends and challenges of UBMDO, sparking innovative thinking and research interests among readers in this field. Multidisciplinary Design Optimization of Complex Structures Under Uncertainty caters to a diverse audience: Engineers specializing in multidisciplinary design optimization are given the tools to master uncertainty management, and researchers in related fields will gain important theoretical insights and practical guidance in uncertainty analysis. Additionally, scholars and educators can utilize the book as a comprehensive resource for advanced courses, enabling students to grasp the latest UBMDO applications. Decision makers and managers handling complex systems can extract methods from the book, facilitating improved risk assessment, and strategic development through uncertainty-based optimization.
| Author | : David Skillicorn |
| Publisher | : CRC Press |
| Total Pages | : 268 |
| Release | : 2007-05-17 |
| Genre | : Computers |
| ISBN | : 1584888334 |
Making obscure knowledge about matrix decompositions widely available, Understanding Complex Datasets: Data Mining with Matrix Decompositions discusses the most common matrix decompositions and shows how they can be used to analyze large datasets in a broad range of application areas. Without having to understand every mathematical detail, the book
| Author | : J.P. Vanden Heuvel |
| Publisher | : Gulf Professional Publishing |
| Total Pages | : 674 |
| Release | : 2002-02-14 |
| Genre | : Business & Economics |
| ISBN | : 9780444508683 |
Volume 14 in the series Comprehensive Toxicology extends and complements the previously published 13-volume set. This volume will be available separately. Toxicology is the study of the nature and actions of chemicals on biological systems. In more primitive times, it really was the study of poisons. However, in the early 1500s, it was apparent to Paracelsus that "the dose differentiates a poison and a remedy". Clearly, the two most important tenets of toxicology were established during that time. The level of exposure (dose) and the duration of exposure (time) will determine the degree and nature of a toxicological response. Since that time the discipline of toxicology has made major advances in identifying and characterizing toxicants. The growth of toxicology as a scientific discipline has been driven to a large extent by the use of extremely powerful molecular and cell biology techniques. The overall aim of this volume is to demonstrate how these advances are being used to elucidate causal pathways (or linkages) for potential adverse health consequences of human exposure to environmental chemicals or radiation. A unique feature of this volume is its illustration of how carefully-designed studies of the molecular mechanisms of chemical action provide not only understanding of the potential toxicity of the chemical under investigation, but also new insights into the functioning of the biological system used as an experimental model. Each chapter contains a listing of major peer-reviewed articles and reviews and useful web-sites. In addition, each chapter contains a broad introductory section that outlines the subsequent sections. These Introductory and Overview sections are designed to be stand alone chapters, and may be packaged as a textbook in graduate level courses.
| Author | : Kumar, A.V. Senthil |
| Publisher | : IGI Global |
| Total Pages | : 448 |
| Release | : 2016-08-12 |
| Genre | : Computers |
| ISBN | : 1522506144 |
Web usage mining is defined as the application of data mining technologies to online usage patterns as a way to better understand and serve the needs of web-based applications. Because the internet has become a central component in information sharing and commerce, having the ability to analyze user behavior on the web has become a critical component to a variety of industries. Web Usage Mining Techniques and Applications Across Industries addresses the systems and methodologies that enable organizations to predict web user behavior as a way to support website design and personalization of web-based services and commerce. Featuring perspectives from a variety of sectors, this publication is designed for use by IT specialists, business professionals, researchers, and graduate-level students interested in learning more about the latest concepts related to web-based information retrieval and mining.
