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Books > Computing & IT > Applications of computing > Databases
Daily procedures such as scientific experiments and business processes have the potential to create a huge amount of data every day, hour, or even second, and this may lead to a major problem for the future of efficient data search and retrieval as well as secure data storage for the world's scientists, engineers, doctors, librarians, and business managers.Design, Performance, and Analysis of Innovative Information Retrieval examines a number of emerging technologies that significantly contribute to modern Information Retrieval (IR), as well as fundamental IR theories and concepts that have been adopted into new tools or systems. This reference is essential to researchers, educators, professionals, and students interested in the future of IR.
The series, Contemporary Perspectives on Data Mining, is composed of blind refereed scholarly research methods and applications of data mining. This series will be targeted both at the academic community, as well as the business practitioner. Data mining seeks to discover knowledge from vast amounts of data with the use of statistical and mathematical techniques. The knowledge is extracted from this data by examining the patterns of the data, whether they be associations of groups or things, predictions, sequential relationships between time order events or natural groups. Data mining applications are in finance (banking, brokerage, and insurance), marketing (customer relationships, retailing, logistics, and travel), as well as in manufacturing, health care, fraud detection, homeland security, and law enforcement.
Research and development surrounding the use of data queries is receiving increased attention from computer scientists and data specialists alike. Through the use of query technology, large volumes of data in databases can be retrieved, and information systems built based on databases can support problem solving and decision making across industries. The Handbook of Research on Innovative Database Query Processing Techniques focuses on the growing topic of database query processing methods, technologies, and applications. Aimed at providing an all-inclusive reference source of technologies and practices in advanced database query systems, this book investigates various techniques, including database and XML queries, spatiotemporal data queries, big data queries, metadata queries, and applications of database query systems. This comprehensive handbook is a necessary resource for students, IT professionals, data analysts, and academicians interested in uncovering the latest methods for using queries as a means to extract information from databases. This all-inclusive handbook includes the latest research on topics pertaining to information retrieval, data extraction, data management, design and development of database queries, and database and XM queries.
Electronic discovery refers to a process in which electronic data
is sought, located, secured, and searched with the intent of using
it as evidence in a legal case. Computer forensics is the
application of computer investigation and analysis techniques to
perform an investigation to find out exactly what happened on a
computer and who was responsible. IDC estimates that the U.S.
market for computer forensics will be grow from $252 million in
2004 to $630 million by 2009. Business is strong outside the United
States, as well. By 2011, the estimated international market will
be $1.8 billion dollars. The Techno Forensics Conference has
increased in size by almost 50% in its second year; another example
of the rapid growth in the market.
An all-star cast of authors analyze the top IT security threats for
2008 as selected by the editors and readers of Infosecurity
Magazine. This book, compiled from the Syngress Security Library,
is an essential reference for any IT professional managing
enterprise security. It serves as an early warning system, allowing
readers to assess vulnerabilities, design protection schemes and
plan for disaster recovery should an attack occur. Topics include
Botnets, Cross Site Scripting Attacks, Social Engineering, Physical
and Logical Convergence, Payment Card Industry (PCI) Data Security
Standards (DSS), Voice over IP (VoIP), and Asterisk Hacking.
The field of data mining is receiving significant attention in today's information-rich society, where data is available from different sources and formats, in large volumes, and no longer constitutes a bottleneck for knowledge acquisition. This rich information has paved the way for novel areas of research, particularly in the crime data analysis realm. Data Mining Trends and Applications in Criminal Science and Investigations presents scientific concepts and frameworks of data mining and analytics implementation and uses across various domains, such as public safety, criminal investigations, intrusion detection, crime scene analysis, and suspect modeling. Exploring the diverse ways that data is revolutionizing the field of criminal science, this publication meets the research needs of law enforcement professionals, data analysts, investigators, researchers, and graduate-level students.
Cluster or co-cluster analyses are important tools in a variety of scientific areas. The introduction of this book presents a state of the art of already well-established, as well as more recent methods of co-clustering. The authors mainly deal with the two-mode partitioning under different approaches, but pay particular attention to a probabilistic approach. Chapter 1 concerns clustering in general and the model-based clustering in particular. The authors briefly review the classical clustering methods and focus on the mixture model. They present and discuss the use of different mixtures adapted to different types of data. The algorithms used are described and related works with different classical methods are presented and commented upon. This chapter is useful in tackling the problem of co-clustering under the mixture approach. Chapter 2 is devoted to the latent block model proposed in the mixture approach context. The authors discuss this model in detail and present its interest regarding co-clustering. Various algorithms are presented in a general context. Chapter 3 focuses on binary and categorical data. It presents, in detail, the appropriated latent block mixture models. Variants of these models and algorithms are presented and illustrated using examples. Chapter 4 focuses on contingency data. Mutual information, phi-squared and model-based co-clustering are studied. Models, algorithms and connections among different approaches are described and illustrated. Chapter 5 presents the case of continuous data. In the same way, the different approaches used in the previous chapters are extended to this situation. Contents 1. Cluster Analysis. 2. Model-Based Co-Clustering. 3. Co-Clustering of Binary and Categorical Data. 4. Co-Clustering of Contingency Tables. 5. Co-Clustering of Continuous Data. About the Authors Gerard Govaert is Professor at the University of Technology of Compiegne, France. He is also a member of the CNRS Laboratory Heudiasyc (Heuristic and diagnostic of complex systems). His research interests include latent structure modeling, model selection, model-based cluster analysis, block clustering and statistical pattern recognition. He is one of the authors of the MIXMOD (MIXtureMODelling) software. Mohamed Nadif is Professor at the University of Paris-Descartes, France, where he is a member of LIPADE (Paris Descartes computer science laboratory) in the Mathematics and Computer Science department. His research interests include machine learning, data mining, model-based cluster analysis, co-clustering, factorization and data analysis. Cluster Analysis is an important tool in a variety of scientific areas. Chapter 1 briefly presents a state of the art of already well-established as well more recent methods. The hierarchical, partitioning and fuzzy approaches will be discussed amongst others. The authors review the difficulty of these classical methods in tackling the high dimensionality, sparsity and scalability. Chapter 2 discusses the interests of coclustering, presenting different approaches and defining a co-cluster. The authors focus on co-clustering as a simultaneous clustering and discuss the cases of binary, continuous and co-occurrence data. The criteria and algorithms are described and illustrated on simulated and real data. Chapter 3 considers co-clustering as a model-based co-clustering. A latent block model is defined for different kinds of data. The estimation of parameters and co-clustering is tackled under two approaches: maximum likelihood and classification maximum likelihood. Hard and soft algorithms are described and applied on simulated and real data. Chapter 4 considers co-clustering as a matrix approximation. The trifactorization approach is considered and algorithms based on update rules are described. Links with numerical and probabilistic approaches are established. A combination of algorithms are proposed and evaluated on simulated and real data. Chapter 5 considers a co-clustering or bi-clustering as the search for coherent co-clusters in biological terms or the extraction of co-clusters under conditions. Classical algorithms will be described and evaluated on simulated and real data. Different indices to evaluate the quality of coclusters are noted and used in numerical experiments.
A fascinating work on the history and development of cryptography, from the Egyptians to WWII. Many of the earliest books, particularly those dating back to the 1900s and before, are now extremely scarce and increasingly expensive. Hesperides Press are republishing these classic works in affordable, high quality, modern editions, using the original text and artwork Contents Include The Beginings of Cryptography From the Middle Ages Onwards Signals, Signs, And Secret Languages Commercial Codes Military Codes and Ciphers Types of Codes and Ciphers Methods of Deciphering Bibliography
As the Internet has evolved to become an integral part of modern society, the need for better quality assurance practices in web engineering has heightened. Adherence to and improvement of current standards ensures that overall web usability and accessibility are at optimum efficiency. Design Solutions for Improving Website Quality and Effectiveness is an authoritative reference source for the latest breakthroughs, techniques, and research-based solutions for the overall improvement of the web designing process. Featuring relevant coverage on the analytics, metrics, usage, and security aspects of web environments, this publication is ideally designed for reference use by engineers, researchers, graduate students, and web designers interested in the enhancement of various types of websites.
In today s information age, the security of digital communication and transactions is of critical importance. Cryptography is the traditional, yet effective, practice of concealing personal information in cyberspace. Applied Cryptography for Cyber Security and Defense: Information Encryption and Cyphering applies the principles of cryptographic systems to real-world scenarios, explaining how cryptography can protect businesses information and ensure privacy for their networks and databases. It delves into the specific security requirements within various emerging application areas and discusses procedures for engineering cryptography into system design and implementation.
Information security is moving much higher up the agenda of corporate concerns. The pitfalls lying in wait of corporate information are legion. If information is our most important asset, then we must fortify ourselves for the task of protecting it properly. This book is a compilation of contributed chapters by researches and practitioners addressing issues, trends and challenges facing the management of information security in this new millennium. Information Security Management: Global Challenges in the New Millennium focuses on aspects of information security planning, evaluation, design and implementation.
This book explores categories of applications and driving factors surrounding the Smart City phenomenon. The contributing authors provide perspective on the Smart Cities, covering numerous applications and classes of applications. The book uses a top-down exploration of the driving factors in Smart Cities, by including focal areas including "Smart Healthcare," "Public Safety & Policy Issues," and "Science, Technology, & Innovation." Contributors have direct and substantive experience with important aspects of Smart Cities and discuss issues with technologies & standards, roadblocks to implementation, innovations that create new opportunities, and other factors relevant to emerging Smart City infrastructures. Features an exploration of Smart City issues and solutions from a variety of stakeholders in the evolving field Presents conversational, nuanced, and forward thinking perspectives on Smart Cities, their implications, limitations, obstacles, and opportunities Includes contributions from industry insiders who have direct, relevant experience with their respective subjects as well as positioning and corporate stature
To develop and sustain competitive advantage in the marketplace, organizations depend critically on competence and resources, knowledge and information exchanged both within and across partner organizations, and on process integration and management. ""Semantic Web Technologies and E-Business: Toward the Integrated Virtual Organization and Business Process Automation"" presents research related to the application of semantic Web technologies, including semantic service-oriented architecture, semantic content management, and semantic knowledge sharing in e-business processes. ""Semantic Web Technologies and E-Business: Toward the Integrated Virtual Organization and Business Process Automation"" compiles research from experts around the globe, bringing business, managerial, technological, and implementation issues surrounding the application of semantic Web technologies in e-business to the forefront.
How to Cheat at Windows Systems Administrators using Command line
scripts teaches system administrators hundreds of powerful,
time-saving tips for automating daily system administration tasks
using Windows command line scripts.
One of the infinite rewards to continuously advancing technology is an increased ease and precision in organizational techniques. Online data collection and online instruments are vital ways to electronically measure and assess organizational areas relevant to management, leadership, and human research development.Online Instruments, Data Collection, and Electronic Measurements: Organizational Advancements aims to assist researchers in both understanding and utilizing online data collection by providing methodological knowledge related to online research, and by presenting information about the empirical quality, the availability, and the location of specific online instruments. This book provides a strong focus on organizational leadership instruments while combining them with practical and ethical issues associated with online data collection. Such a combination makes this a unique contribution to the field.
As technology continues to become more sophisticated, mimicking natural processes and phenomena becomes more of a reality. Continued research in the field of natural computing enables an understanding of the world around us, in addition to opportunities for manmade computing to mirror the natural processes and systems that have existed for centuries. Nature-Inspired Algorithms for Big Data Frameworks is a collection of innovative research on the methods and applications of extracting meaningful information from data using algorithms that are capable of handling the constraints of processing time, memory usage, and the dynamic and unstructured nature of data. Highlighting a range of topics including genetic algorithms, data classification, and wireless sensor networks, this book is ideally designed for computer engineers, software developers, IT professionals, academicians, researchers, and upper-level students seeking current research on the application of nature and biologically inspired algorithms for handling challenges posed by big data in diverse environments.
The Semantic Web combines the descriptive languages RDF (Resource Description Framework) and OWL (Web Ontology Language), with the data-centric, customizable XML (eXtensible Mark-up Language) to provide descriptions of the content of Web documents. These machine-interpretable descriptions allow more intelligent software systems to be written, automating the analysis and exploitation of web-based information. Software agents will be able to create "automatically" new services from already published services, with potentially huge implications for models of e-Business. "Semantic Web Technologies" provides a comprehensive overview of key semantic knowledge technologies and research. The authors explain (semi-)automatic ontology generation and metadata extraction in depth, along with ontology management and mediation. Further chapters examine how Semantic Web technology is being applied in knowledge management ("Semantic Information Access") and in the next generation of Web services. "Semantic Web Technologies: " Provides a comprehensive exposition of the state-of-the art in Semantic Web research and key technologies. Explains the use of ontologies and metadata to achieve machine-interpretability. Describes methods for ontology learning and metadata generation. Discusses ontology management and evolution, covering ontology change detection and propagation, ontology dependency and mediation. Illustrates the theoretical concepts with three case studies on industrial applications in digital libraries, the legal sector and the telecommunication industry. Graduate and advanced undergraduate students, academic and industrial researchers in the field will all find "Semantic WebTechnologies" an essential guide to the technologies of the Semantic Web.
Acclaimed by various content platforms (books, music, movies) and auction sites online, recommendation systems are key elements of digital strategies. If development was originally intended for the performance of information systems, the issues are now massively moved on logical optimization of the customer relationship, with the main objective to maximize potential sales. On the transdisciplinary approach, engines and recommender systems brings together contributions linking information science and communications, marketing, sociology, mathematics and computing. It deals with the understanding of the underlying models for recommender systems and describes their historical perspective. It also analyzes their development in the content offerings and assesses their impact on user behavior.
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