Data science in theory and practice : Techniques for big data analytics and complex data sets
Delivers a comprehensive treatment of the mathematical and statistical models useful for analyzing data sets arising in various disciplines, like banking, finance, health care, bioinformatics, security, education, and social services. Written in five parts, the book examines some of the most commonly used and fundamental mathematical and statistical concepts that form the basis of data science. The authors go on to analyze various data transformation techniques useful for extracting information from raw data, long memory behavior, and predictive modeling. Readers will also learn from topics like: Analyses of foundational theoretical subjects, including the history of data science, matrix algebra and random vectors, and multivariate analysis A comprehensive examination of time series forecasting, including the different components of time series and transformations to achieve stationarity Introductions to both the R and Python programming languages, including basic data types and sample manipulations for both languages An exploration of algorithms, including how to write one and how to perform an asymptotic analysis A comprehensive discussion of several techniques for analyzing and predicting complex data sets
Data Science ; 6th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2020, Taiyuan, China, September 18-21, 2020, Proceedings, Part I
This two volume set (CCIS 1257 and 1258) constitutes the refereed proceedings of the 6th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2020 held in Taiyuan, China, in September 2020. The 98 papers presented in these two volumes were carefully reviewed and selected from 392 submissions. The papers are organized in topical sections: database, machine learning, network, graphic images, system, natural language processing, security, algorithm, application, and education.
Data Quality and Record Linkage Techniques
This book helps practitioners gain a deeper understanding, at an applied level, of the issues involved in improving data quality through editing, imputation, and record linkage. The first part of the book deals with methods and models. Here, we focus on the Fellegi-Holt edit-imputation model, the Little-Rubin multiple-imputation scheme, and the Fellegi-Sunter record linkage model. Brief examples are included to show how these techniques work. In the second part of the book, the authors present real-world case studies in which one or more of these techniques are used. They cover a wide variety of application areas. These include mortgage guarantee insurance, medical, biomedical, highway safety, and social insurance as well as the construction of list frames and administrative lists.
Data Quality : Concepts, Methodologies and Techniques
Batini and Scannapieco present a comprehensive and systematic introduction to the wide set of issues related to data quality. They start with a detailed description of different data quality dimensions, like accuracy, completeness, and consistency, and their importance in different types of data, like federated data, web data, or time-dependent data, and in different data categories classified according to frequency of change, like stable, long-term, and frequently changing data. The book's extensive description of techniques and methodologies from core data quality research as well as from related fields like data mining, probability theory, statistical data analysis, and machine learning gives an excellent overview of the current state of the art.
Data mining with computational intelligence
Finding information hidden in data is as theoretically difficult as it is practically important. With the objective of discovering unknown patterns from data, the methodologies of data mining were derived Wang and Fu present in detail the state of the art on how to utilize fuzzy neural networks, multilayer perceptron neural networks, radial basis function neural networks, genetic algorithms, and support vector machines in such applications. They focus on three main data mining tasks: data dimensionality reduction, classification, and rule extraction. The book is targeted at researchers in both academia and industry, while graduate students and developers of data mining systems will also profit from the detailed algorithmic descriptions.
Data mining and machine learning applications
Elaborates in detail on the current needs of data mining and machine learning and promotes mutual understanding among research in different disciplines, thus facilitating research development and collaboration. Data, the latest currency of today’s world, is the new gold. In this new form of gold, the most beautiful jewels are data analytics and machine learning. Data mining and machine learning are considered interdisciplinary fields. Data mining is a subset of data analytics and machine learning involves the use of algorithms that automatically improve through experience based on data.
Data mining and Knowledge discovery handbook
Data Mining and Knowledge Discovery Handbook organizes all major concepts, theories, methodologies, trends, challenges and applications of data mining (DM) and knowledge discovery in databases (KDD) into a coherent and unified repository. This book first surveys, then provides comprehensive yet concise algorithmic descriptions of methods, including classic methods plus the extensions and novel methods developed recently. This volume concludes with in-depth descriptions of data mining applications in various interdisciplinary industries including finance, marketing, medicine, biology, engineering, telecommunications, software, and security.
Data Mining and Diagnosing IC Fails
This book brings together a large number of analysis techniques that are suitable for IC fail data, but that are not available elsewhere in a single place. Several of the techniques, in fact, have been presented only recently in technical conferences. The purpose of the book is to bring together in one place a large number of analysis, data mining and diagnosis techniques that have proven to be useful in analyzing IC fails. The descriptions of the techniques and analysis routines is sufficiently detailed that profession manufacturing engineers can implement them in their own work environment
Data management in a connected world : Essays dedicated to Hartmut Wedekind on the occasion of his 70th birthday
Data management systems play the most crucial role in building large application s- tems. Since modern applications are no longer single monolithic software blocks but highly flexible and configurable collections of cooperative services, the data mana- ment layer also has to adapt to these new requirements. Therefore, within recent years, data management systems have faced a tremendous shift from the central management of individual records in a transactional way to a platform for data integration, fede- tion, search services, and data analysis. This book addresses these new issues in the area of data management from multiple perspectives, in the form of individual contributions, and it outlines future challenges in the context of data management.
Data Compression : The Complete Reference
This book of Data Compression provides an all-inclusive, thoroughly updated, and user-friendly reference for the many different types and methods of compression (especially audio compression, an area in which many new topics covered in this revised edition appear). Among the important features of the book are a detailed and helpful taxonomy, a detailed description of the most common methods, and discussions on the use and comparative benefits of different methods. The book’s logical, clear and lively presentation is organized around the main branches of data compression.
Data Complexity in Pattern Recognition
Data Complexity in Pattern Recognition is unique in its comprehensive coverage and multidisciplinary approach from various methodological and practical perspectives. Researchers and practitioners alike will find this book an insightful reference to learn about the current status of available techniques as well as application areas.
Data Communications and Networking with TCP
Teaches the principles of networking using TCP/IP protocol suite. It employs a bottom-up approach where each layer in the TCP/IP protocol suite is built on the services provided by the layer below.
Data Communications and networking
Helps students understand the basics of data communications and networking, and the protocols used in the Internet in particular by using the protocol layering of the Internet and TCP/IP protocol suite. Technologies related to data communication and networking may be the fastest growing in today's culture.
Data communications and network technologies
Aims to help readers master the basics of network communications and use Huawei network devices to set up enterprise LANs and WANs, wired networks, and wireless networks, ensure network security for enterprises, and grasp cutting-edge computer network technologies. The content of this book includes: network communication fundamentals, TCP/IP protocol, Huawei VRP operating system, IP addresses and subnetting, static and dynamic routing, Ethernet networking technology, ACL and AAA, network address translation, DHCP server, WLAN, IPv6, WAN PPP and PPPoE protocol, typical networking architecture and design cases of campus networks, SNMP protocol used by network management, operation and maintenance, network time protocol NTP, SND and NFV, programming, and automation.
Data augmented design : Embracing new data for sustainable urban planning and design
This book offers an essential introduction to a new urban planning and design methodology called Data Augmented Design (DAD) and its evolution and progresses, highlighting data driven methods, urban planning and design applications and related theories. The authors draw on many kinds of data, including big, open, and conventional data, and discuss cutting-edge technologies that illustrate DAD as a future-oriented design framework in terms of its focus on multi-data, multi-method, multi-stage and multi-scale sustainable urban planning. In four sections and ten chapters, the book presents case studies to address the core concepts of DAD, the first type of applications of DAD that emerged in redevelopment-oriented planning and design, the second type committed to the planning and design for urban expansion, and the future-oriented applications of DAD to advance sustainable technologies and the future structural form of the built environment. The book is geared towards a broad readership, ranging from researchers and students of urban planning, urban design, urban geography, urban economics, and urban sociology, to practitioners in the areas of urban planning and design.
Data and Computer Communications
It is ideal for one/two-semester courses in Computer Networks, Data Communications, and Communications Networks in CS, CIS, and Electrical Engineering departments. This book is also suitable for Product Development personnel, Programmers, Systems Engineers, Network Designers and others involved in the design of data communications and networking products. With a focus on the most current technology and a convenient modular format, this best-selling text offers a clear and comprehensive survey of the entire data and computer communications field. Emphasizing both the fundamental principles as well as the critical role of performance in driving protocol and network design, it explores in detail all the critical technical areas in data communications, wide-area networking, local area networking, and protocol design.
Data and applications security XXII ; 22nd Annual IFIP WG 11.3 Working Conference on data and applications security London, UK, July 13-16, 2008 Proceedings
This volume contains the papers presented at the 22nd Annual IFIP WG 11.3 Working Conference on Data and Applications Security (DBSEC) held in L- don, UK, July 13–16, 2008.
Data and applications security XXI ; 21st Annual IFIP WG 11.3 Working Conference on data and applications security, Redondo Beach, CA, USA, July 8-11, 2007, Proceedings
This book presented secure query evaluation, location-based security/mobile security, distributed security issues, cryptographic-based security, temporal access control and usage control, as well as system security issues.
Data and applications security XX ; 20th Annual IFIP WG 11.3 Working Conference on data and applications security, Sophia Antipolis, France, July 31-August 2, 2006, Proceedings
For 20 years, the IFIP WG 11. 3 Working Conference on Data and Appli- tions Security (DBSEC) has been a major forum for presenting originalresearch results, practical experiences, and innovative ideas in data and applications - curity.Like the previous conference, the 20th DBSEC has proved to be up to this challenge. DBSEC 2006 received 56 submissions, out of which the program committee selected22 high-qualitypaperscoveringanumber of diverseresearchtopicssuch as access control, privacy, and identity management.
Data and applications security XIX ; 19th Annual IFIP WG 11.3 working conference on data and applications security, Storrs, CT, USA, August 7-10, 2005, Proceedings
Constitutes the refereed proceedings of the 19th Annual Working Conference on Data and Applications Security held in Storrs, CT, USA, in August 2005. The papers present theory, technique, applications, and practical experience of data and application security with topics like cryptography, privacy, security planning and administration, and more.



















