Author: Hanan Samet
Publisher: Morgan Kaufmann
Samet offers a thorough treatment of multidimensional point data, object and image-based representations, intervals and small rectangles, and high-dimensional datasets. This work includes a thorough introduction; a comprehensive survey to spatial and multidimensional data structures and algorithms; and implementation details for the most useful data structures.
XQuery, XPath, and SQL/XML in context
Author: Jim Melton,Stephen Buxton
Publisher: Morgan Kaufmann
XML has become the lingua franca for representing business data, for exchanging information between business partners and applications, and for adding structure– and sometimes meaning—to text-based documents. XML offers some special challenges and opportunities in the area of search: querying XML can produce very precise, fine-grained results, if you know how to express and execute those queries. For software developers and systems architects: this book teaches the most useful approaches to querying XML documents and repositories. This book will also help managers and project leaders grasp how “querying XML fits into the larger context of querying and XML. Querying XML provides a comprehensive background from fundamental concepts (What is XML?) to data models (the Infoset, PSVI, XQuery Data Model), to APIs (querying XML from SQL or Java) and more. * Presents the concepts clearly, and demonstrates them with illustrations and examples; offers a thorough mastery of the subject area in a single book. * Provides comprehensive coverage of XML query languages, and the concepts needed to understand them completely (such as the XQuery Data Model). * Shows how to query XML documents and data using: XPath (the XML Path Language); XQuery, soon to be the new W3C Recommendation for querying XML; XQuery's companion XQueryX; and SQL, featuring the SQL/XML * Includes an extensive set of XQuery, XPath, SQL, Java, and other examples, with links to downloadable code and data samples.
Author: Mikhail Gromov
Publisher: Springer Science & Business Media
This book is an English translation of the famous "Green Book" by Lafontaine and Pansu (1979). It has been enriched and expanded with new material to reflect recent progress. Additionally, four appendices, by Gromov on Levy's inequality, by Pansu on "quasiconvex" domains, by Katz on systoles of Riemannian manifolds, and by Semmes overviewing analysis on metric spaces with measures, as well as an extensive bibliography and index round out this unique and beautiful book.
Author: Jeffrey Scott Vitter
Publisher: Now Publishers Inc
Algorithms and Data Structures for External Memory describes several useful paradigms for the design and implementation of efficient external memory (EM) algorithms and data structures. The problem domains considered include sorting, permuting, FFT, scientific computing, computational geometry, graphs, databases, geographic information systems, and text and string processing.
Author: Aditya P Mathur
Publisher: Pearson Education India
This edition of Foundations of Software Testing is aimed at the undergraduate, the graduate students and the practicing engineers. It presents sound engineering approaches for test generation, ion, minimization, assessment, and enhancement. Using numerous examples, it offers a lucid description of a wide range of simple to complex techniques for a variety of testing-related tasks. It also discusses the comparative analyses of commercially available testing tools to facilitate the tool ion.
Analysis, Visualization and Dashboards
Author: Jay Jacobs,Bob Rudis
Publisher: John Wiley & Sons
Uncover hidden patterns of data and respond with countermeasures Security professionals need all the tools at their disposal to increase their visibility in order to prevent security breaches and attacks. This careful guide explores two of the most powerful ? data analysis and visualization. You'll soon understand how to harness and wield data, from collection and storage to management and analysis as well as visualization and presentation. Using a hands-on approach with real-world examples, this book shows you how to gather feedback, measure the effectiveness of your security methods, and make better decisions. Everything in this book will have practical application for information security professionals. Helps IT and security professionals understand and use data, so they can thwart attacks and understand and visualize vulnerabilities in their networks Includes more than a dozen real-world examples and hands-on exercises that demonstrate how to analyze security data and intelligence and translate that information into visualizations that make plain how to prevent attacks Covers topics such as how to acquire and prepare security data, use simple statistical methods to detect malware, predict rogue behavior, correlate security events, and more Written by a team of well-known experts in the field of security and data analysis Lock down your networks, prevent hacks, and thwart malware by improving visibility into the environment, all through the power of data and Security Using Data Analysis, Visualization, and Dashboards.
Author: Cody S. Ding
Category: Social Science
This book explores the fundamentals of multidimensional scaling (MDS) and how this analytic method can be used in applied setting for educational and psychological research. The book tries to make MDS more accessible to a wider audience in terms of the language and examples that are more relevant to educational and psychological research and less technical so that the readers are not overwhelmed by equations. The goal is for readers to learn the methods described in this book and immediately start using MDS via available software programs. The book also examines new applications that have previously not been discussed in MDS literature. It should be an ideal book for graduate students and researchers to better understand MDS. Fundamentals of Applied Multidimensional Scaling for Educational and Psychological Research is divided into three parts. Part I covers the basic and fundamental features of MDS models pertaining to applied research applications. Chapters in this section cover the essential features of data that are typically associated with MDS analysis such as preference ration or binary choice data, and also looking at metric and non-metric MDS models to build a foundation for later discussion and applications in later chapters. Part II examines specific MDS models and its applications for education and psychology. This includes spatial analysis methods that can be used in MDS to test clustering effect of items and individual differences MDS model (INDSCAL). Finally, Part III focuses on new applications of MDS analysis in these research fields. These new applications consist of profile analysis, longitudinal analysis, mean-level change, and pattern change. The book concludes with a historical review of MDS development as an analytical method and a look to future directions.
Author: Clifford A. Shaffer
Publisher: Courier Corporation
Comprehensive treatment focuses on creation of efficient data structures and algorithms and selection or design of data structure best suited to specific problems. This edition uses C++ as the programming language.
Author: Michel-Marie Deza,Elena Deza
This book comes out of need and urgency (expressed especially in areas of Information Retrieval with respect to Image, Audio, Internet and Biology) to have a working tool to compare data. The book will provide powerful resource for all researchers using Mathematics as well as for mathematicians themselves. In the time when over-specialization and terminology fences isolate researchers, this Dictionary try to be "centripedal" and "oikoumeni", providing some access and altitude of vision but without taking the route of scientific vulgarisation. This attempted balance is the main philosophy of this Dictionary which defined its structure and style. Key features: - Unicity: it is the first book treating the basic notion of Distance in whole generality. - Interdisciplinarity: this Dictionary is larger in scope than majority of thematic dictionaries. - Encyclopedicity: while an Encyclopedia of Distances seems now too difficult to produce, this book (by its scope, short introductions and organization) provides the main material for it and for future tutorials on some parts of this material. - Applicability: the distances, as well as distance-related notions and paradigms, are provided in ready-to-use fashion. - Worthiness: the need and urgency for such dictionary was great in several huge areas, esp. Information Retrieval, Image Analysis, Speech Recognition and Biology. - Accessibility: the definitions are easy to locate by subject or, in Index, by alphabetic order; the introductions and definitions are reader-friendly and maximally independent one from another; still the text is structured, in the 3D HTML style, by hyperlink-like boldfaced references to similar definitions. * Covers a large range of subjects in pure and applied mathematics * Designed to be easily applied--the distances and distance-related notions and paradigms are ready to use * Helps users quickly locate definitions by subject or in alphabetical order; stand-alone entries include references to other entries and sources for further investigation
A Comprehensive Guide for IT Professionals
Author: Paulraj Ponniah
Publisher: John Wiley & Sons
Geared to IT professionals eager to get into the all-important field of data warehousing, this book explores all topics needed by those who design and implement data warehouses. Readers will learn about planning requirements, architecture, infrastructure, data preparation, information delivery, implementation, and maintenance. They'll also find a wealth of industry examples garnered from the author's 25 years of experience in designing and implementing databases and data warehouse applications for major corporations. Market: IT Professionals, Consultants.
Author: Jiawei Han,Jian Pei,Micheline Kamber
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
Mathematics of Perception
Author: Edward Y. Chang
Publisher: Springer Science & Business Media
"Foundations of Large-Scale Multimedia Information Management and Retrieval: Mathematics of Perception" covers knowledge representation and semantic analysis of multimedia data and scalability in signal extraction, data mining, and indexing. The book is divided into two parts: Part I - Knowledge Representation and Semantic Analysis focuses on the key components of mathematics of perception as it applies to data management and retrieval. These include feature selection/reduction, knowledge representation, semantic analysis, distance function formulation for measuring similarity, and multimodal fusion. Part II - Scalability Issues presents indexing and distributed methods for scaling up these components for high-dimensional data and Web-scale datasets. The book presents some real-world applications and remarks on future research and development directions. The book is designed for researchers, graduate students, and practitioners in the fields of Computer Vision, Machine Learning, Large-scale Data Mining, Database, and Multimedia Information Retrieval. Dr. Edward Y. Chang was a professor at the Department of Electrical & Computer Engineering, University of California at Santa Barbara, before he joined Google as a research director in 2006. Dr. Chang received his M.S. degree in Computer Science and Ph.D degree in Electrical Engineering, both from Stanford University.
Algorithms and Applications
Author: S. Muthukrishnan
Publisher: Now Publishers Inc
In the data stream scenario, input arrives very rapidly and there is limited memory to store the input. Algorithms have to work with one or few passes over the data, space less than linear in the input size or time significantly less than the input size. In the past few years, a new theory has emerged for reasoning about algorithms that work within these constraints on space, time, and number of passes. Some of the methods rely on metric embeddings, pseudo-random computations, sparse approximation theory and communication complexity. The applications for this scenario include IP network traffic analysis, mining text message streams and processing massive data sets in general. Researchers in Theoretical Computer Science, Databases, IP Networking and Computer Systems are working on the data stream challenges
From the Science Citation Index to Cybermetrics
Author: Nicola De Bellis
Publisher: Scarecrow Press
Category: Language Arts & Disciplines
Can the methods of science be directed toward science itself? How did it happen that scientists, scientific documents, and their bibliographic links came to be regarded as mathematical variables in abstract models of scientific communication? What is the role of quantitative analyses of scientific and technical documentation in current science policy and management? Bibliometrics and Citation Analysis: From the Science Citation Index to Cybermetrics answers these questions through a comprehensive overview of theories, techniques, concepts, and applications in the interdisciplinary and steadily growing field of bibliometrics. Since citation indexes came into the limelight during the mid-1960s, citation networks have become increasingly important for many different research fields. The book begins by investigating the empirical, philosophical, and mathematical foundations of bibliometrics, including its beginnings with the Science Citation Index, the theoretical framework behind it, and its mathematical underpinnings. It then examines the application of bibliometrics and citation analysis in the sciences and science studies, especially the sociology of science and science policy. Finally it provides a view of the future of bibliometrics, exploring in detail the ongoing extension of bibliometric methods to the structure and dynamics of the World Wide Web. This book gives newcomers to the field of bibliometrics an accessible entry point to an entire research tradition otherwise scattered through a vast amount of journal literature. At the same time, it brings to the forefront the cross-disciplinary linkages between the various fields (sociology, philosophy, mathematics, politics) that intersect at the crossroads of citation analysis. Because of its discursive and interdisciplinary approach, the book is useful to those in every area of scholarship involved in the quantitative analysis of information exchanges, but also to science historians and general readers who simply wish to familiarize them
Algorithms and Applications
Author: Richard Szeliski
Humans perceive the three-dimensional structure of the world with apparent ease. However, despite all of the recent advances in computer vision research, the dream of having a computer interpret an image at the same level as a two-year old remains elusive. Why is computer vision such a challenging problem and what is the current state of the art? Computer Vision: Algorithms and Applications explores the variety of techniques commonly used to analyze and interpret images. It also describes challenging real-world applications where vision is being successfully used, both for specialized applications such as medical imaging, and for fun, consumer-level tasks such as image editing and stitching, which students can apply to their own personal photos and videos. More than just a source of “recipes,” this exceptionally authoritative and comprehensive textbook/reference also takes a scientific approach to basic vision problems, formulating physical models of the imaging process before inverting them to produce descriptions of a scene. These problems are also analyzed using statistical models and solved using rigorous engineering techniques Topics and features: structured to support active curricula and project-oriented courses, with tips in the Introduction for using the book in a variety of customized courses; presents exercises at the end of each chapter with a heavy emphasis on testing algorithms and containing numerous suggestions for small mid-term projects; provides additional material and more detailed mathematical topics in the Appendices, which cover linear algebra, numerical techniques, and Bayesian estimation theory; suggests additional reading at the end of each chapter, including the latest research in each sub-field, in addition to a full Bibliography at the end of the book; supplies supplementary course material for students at the associated website, http://szeliski.org/Book/. Suitable for an upper-level undergraduate or graduate-level course in computer science or engineering, this textbook focuses on basic techniques that work under real-world conditions and encourages students to push their creative boundaries. Its design and exposition also make it eminently suitable as a unique reference to the fundamental techniques and current research literature in computer vision.
Author: Richard H. Bartels,John C. Beatty,Brian A. Barsky
Publisher: Morgan Kaufmann
As the field of computer graphics develops, techniques for modeling complex curves and surfaces are increasingly important. A major technique is the use of parametric splines in which a curve is defined by piecing together a succession of curve segments, and surfaces are defined by stitching together a mosaic of surface patches. An Introduction to Splines for Use in Computer Graphics and Geometric Modeling discusses the use of splines from the point of view of the computer scientist. Assuming only a background in beginning calculus, the authors present the material using many examples and illustrations with the goal of building the reader's intuition. Based on courses given at the University of California, Berkeley, and the University of Waterloo, as well as numerous ACM Siggraph tutorials, the book includes the most recent advances in computer-aided geometric modeling and design to make spline modeling techniques generally accessible to the computer graphics and geometric modeling communities.
Useful Techniques from Sorting to Encryption
Author: Kyle Loudon
Publisher: "O'Reilly Media, Inc."
There are many books on data structures and algorithms, including some with useful libraries of C functions. Mastering Algorithms with C offers you a unique combination of theoretical background and working code. With robust solutions for everyday programming tasks, this book avoids the abstract style of most classic data structures and algorithms texts, but still provides all of the information you need to understand the purpose and use of common programming techniques. Implementations, as well as interesting, real-world examples of each data structure and algorithm, are included. Using both a programming style and a writing style that are exceptionally clean, Kyle Loudon shows you how to use such essential data structures as lists, stacks, queues, sets, trees, heaps, priority queues, and graphs. He explains how to use algorithms for sorting, searching, numerical analysis, data compression, data encryption, common graph problems, and computational geometry. And he describes the relative efficiency of all implementations. The compression and encryption chapters not only give you working code for reasonably efficient solutions, they offer explanations of concepts in an approachable manner for people who never have had the time or expertise to study them in depth. Anyone with a basic understanding of the C language can use this book. In order to provide maintainable and extendible code, an extra level of abstraction (such as pointers to functions) is used in examples where appropriate. Understanding that these techniques may be unfamiliar to some programmers, Loudon explains them clearly in the introductory chapters. Contents include: Pointers Recursion Analysis of algorithms Data structures (lists, stacks, queues, sets, hash tables, trees, heaps, priority queues, graphs) Sorting and searching Numerical methods Data compression Data encryption Graph algorithms Geometric algorithms
The Metric Space Approach
Author: Pavel Zezula,Giuseppe Amato,Vlastislav Dohnal,Michal Batko
Publisher: Springer Science & Business Media
The area of similarity searching is a very hot topic for both research and c- mercial applications. Current data processing applications use data with c- siderably less structure and much less precise queries than traditional database systems. Examples are multimedia data like images or videos that offer query by example search, product catalogs that provide users with preference based search, scientific data records from observations or experimental analyses such as biochemical and medical data, or XML documents that come from hetero- neous data sources on the Web or in intranets and thus does not exhibit a global schema. Such data can neither be ordered in a canonical manner nor meani- fully searched by precise database queries that would return exact matches. This novel situation is what has given rise to similarity searching, also - ferred to as content based or similarity retrieval. The most general approach to similarity search, still allowing construction of index structures, is modeled in metric space. In this book. Prof. Zezula and his co authors provide the first monograph on this topic, describing its theoretical background as well as the practical search tools of this innovative technology.
Author: Michael T. Goodrich,Roberto Tamassia,Michael H. Goldwasser
Publisher: Wiley Global Education
Based on the authors market leading data structures books in Java and C++, this textbook offers a comprehensive, definitive introduction to data structures in Python by authoritative authors. Data Structures and Algorithms in Python is the first authoritative object-oriented book available for the Python data structures course. Designed to provide a comprehensive introduction to data structures and algorithms, including their design, analysis, and implementation, the text will maintain the same general structure as Data Structures and Algorithms in Java and Data Structures and Algorithms in C++.