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Books > Computing & IT > Applications of computing > Databases
This book constitutes the refereed proceedings of the 4th IFIP WG 8.1 Working Conference on Method Engineering, ME 2011, held in Paris, France, in April 2011. The 13 revised full papers and 6 short papers presented together with the abstracts of two keynote talks were carefully reviewed and selected from 30 submissions. The papers are organized in topical sections on situated method engineering, method engineering foundations, customized methods, tools for method engineering, new trends to build methods, and method engineering services.
In this book, the editors explain how students enrolled in two digital forensic courses at their institution are exposed to experiential learning opportunities, where the students acquire the knowledge and skills of the subject-matter while also learning how to adapt to the ever-changing digital forensic landscape. Their findings (e.g., forensic examination of different IoT devices) are also presented in the book. Digital forensics is a topic of increasing importance as our society becomes "smarter" with more of the "things" around us been internet- and inter-connected (e.g., Internet of Things (IoT) and smart home devices); thus, the increasing likelihood that we will need to acquire data from these things in a forensically sound manner. This book is of interest to both digital forensic educators and digital forensic practitioners, as well as students seeking to learn about digital forensics.
Fuzzy Cluster Analysis presents advanced and powerful fuzzy clustering techniques. This thorough and self-contained introduction to fuzzy clustering methods and applications covers classification, image recognition, data analysis and rule generation. Combining theoretical and practical perspectives, each method is analysed in detail and fully illustrated with examples. Features include:
This book sheds new light on the current and future challenges faced by cities, and presents approaches, options and solutions enabled by Information and Communication Technologies (ICT) in the smart city context. By focusing on sustainability objectives within a rapidly changing social, economic, environmental and technological setting, it explores a variety of planning challenges faced by contemporary cities and the power of smart city developments in terms of providing innovative tools, approaches, methodologies and technologies to help cities cope with these challenges. Key issues addressed include smart city (e-) planning and (e-)participation; smart data management to facilitate decision-making processes in cities and insular communities on a variety of topics; smart and sustainable management aspects of climate change, water scarcity, mobility, energy, infrastructure, tourism, blue growth, risk assessment; etc. The book presents current and potential pathways and applications for the evolution of smart cities and communities, taking into consideration the unique problems and opportunities emanating from their specific geographical location. The case study examples mainly concern small and medium-sized cities and communities as well as insular areas in the Mediterranean region, while also incorporating lessons learned from other parts of the world. Their focus is on the specific opportunities and threats emerging in these urban and insular environments, which are characterized by their role as globally known tourist destinations, their coastal or port character, and unique cultural resources, as well as the high rated vulnerability in very many sustainability respects (social, economic, biodiversity, urbanization, migration, poverty, etc.) to be found in the Mediterranean region at large
The book describes the emergence of big data technologies and the role of Spark in the entire big data stack. It compares Spark and Hadoop and identifies the shortcomings of Hadoop that have been overcome by Spark. The book mainly focuses on the in-depth architecture of Spark and our understanding of Spark RDDs and how RDD complements big data's immutable nature, and solves it with lazy evaluation, cacheable and type inference. It also addresses advanced topics in Spark, starting with the basics of Scala and the core Spark framework, and exploring Spark data frames, machine learning using Mllib, graph analytics using Graph X and real-time processing with Apache Kafka, AWS Kenisis, and Azure Event Hub. It then goes on to investigate Spark using PySpark and R. Focusing on the current big data stack, the book examines the interaction with current big data tools, with Spark being the core processing layer for all types of data. The book is intended for data engineers and scientists working on massive datasets and big data technologies in the cloud. In addition to industry professionals, it is helpful for aspiring data processing professionals and students working in big data processing and cloud computing environments.
When digitized entities, connected devices and microservices interact purposefully, we end up with a massive amount of multi-structured streaming (real-time) data that is continuously generated by different sources at high speed. Streaming analytics allows the management, monitoring, and real-time analytics of live streaming data. The topic has grown in importance due to the emergence of online analytics and edge and IoT platforms. A real digital transformation is being achieved across industry verticals through meticulous data collection, cleansing and crunching in real time. Capturing and subjecting those value-adding events is considered to be the prime task for achieving trustworthy and timely insights. The authors articulate and accentuate the challenges widely associated with streaming data and analytics, describe data analytics algorithms and approaches, present edge and fog computing concepts and technologies and show how streaming analytics can be accomplished in edge device clouds. They also delineate several industry use cases across cloud system operations in transportation and cyber security and other business domains. The book will be of interest to ICTs industry and academic researchers, scientists and engineers as well as lecturers and advanced students in the fields of data science, cloud/fog/edge architecture, internet of things and artificial intelligence and related fields of applications. It will also be useful to cloud/edge/fog and IoT architects, analytics professionals, IT operations teams and site reliability engineers (SREs).
As economies continue to evolve, knowledge is being recognized as a business asset and considered a crucial component of business strategy. The ability to manage knowledge is increasingly important for securing and maintaining organizational success and surviving in the knowledge economy. ""Knowledge Management Strategies for Business Development"" addresses the relevance of knowledge management strategies for the advancement of organizations worldwide. This reference book supplies business practitioners, academicians, and researchers with comprehensive tools to systematically guide through a process that focuses on data gathering, analysis, and decision making.
A paradigm shift is taking place in computer science: one generation ago, we learned to abstract from hardware to software, now we are abstracting from software to serviceware implemented through service-oriented computing. Yet ensuring interoperability in open, heterogeneous, and dynamically changing environments, such as the Internet, remains a major challenge for actual machine-to-machine integration. Usually significant problems in aligning data, processes, and protocols appear as soon as a specific piece of functionality is used within a different application context. The Semantic Web Services (SWS) approach is about describing services with metadata on the basis of domain ontologies as a means to enable their automatic location, execution, combination, and use. Fensel and his coauthors provide a comprehensive overview of SWS in line with actual industrial practice. They introduce the main sociotechnological components that ground the SWS vision (like Web Science, Service Science, and service-oriented architectures) and several approaches that realize it, e.g. the Web Service Modeling Framework, OWL-S, and RESTful services. The real-world relevance is emphasized through a series of case studies from large-scale R&D projects and a business-oriented proposition from the SWS technology provider Seekda. Each chapter of the book is structured according to a predefined template, covering both theoretical and practical aspects, and including walk-through examples and hands-on exercises. Additional learning material is available on the book website www.swsbook.org. With its additional features, the book is ideally suited as the basis for courses or self-study in this field, and it may also serve as a reference for researchers looking for a state-of-the-art overview of formalisms, methods, tools, and applications related to SWS."
Logic and the Organization of Information closely examines the
historical and contemporary methodologies used to catalogue
information objects-books, ebooks, journals, articles, web pages,
images, emails, podcasts and more-in the digital era.
This book provides extensive insight into the possibilities and challenges of XML in building new information management solutions in networked organizations. After a brief introduction to Web communication features and XML fundamentals, the book examines the benefits of adopting XML and illustrates various types of XML use: XML in document management; XML for data-centric and multimedia components; XML as a format for metadata, including metadata for the Semantic Web; and XML in support of data interchange between software applications and among organizations. The challenges of adopting XML in large-scale information management are also discussed. In addition, applications across a broad spectrum are examined and numerous case studies pertaining to the adoption of XML are presented. The book is particularly suitable for courses offered in Information Studies, Information Systems, or Information Technology. It also serves as an excellent practical guide for professionals in information management and provides important support material for courses in Computer Science and in Business.
Recently, researchers have gained innovative principles, methods, algorithms, and solutions to challenging problems faced in the development of data warehousing, knowledge discovery, and data mining applications. Complex Data Warehousing and Knowledge Discovery for Advanced Retrieval Development: Innovative Methods and Applications provides a comprehensive analysis on current issues and trends in retrieval expansion. Containing research from leading international experts, this book presents future challenges and opportunities in the field valuable to academicians, researchers, and practitioners.
This book covers diverse aspects of advanced computer and communication engineering, focusing specifically on industrial and manufacturing theory and applications of electronics, communications, computing and information technology. Experts in research, industry, and academia present the latest developments in technology, describe applications involving cutting-edge communication and computer systems and explore likely future directions. In addition, access is offered to numerous new algorithms that assist in solving computer and communication engineering problems. The book is based on presentations delivered at ICOCOE 2014, the 1st International Conference on Communication and Computer Engineering. It will appeal to a wide range of professionals in the field, including telecommunication engineers, computer engineers and scientists, researchers, academics and students.
This book addresses the impacts of various types of services such as infrastructure, platforms, software, and business processes that cloud computing and Big Data have introduced into business. Featuring chapters which discuss effective and efficient approaches in dealing with the inherent complexity and increasing demands in data science, a variety of application domains are covered. Various case studies by data management and analysis experts are presented in these chapters. Covered applications include banking, social networks, bioinformatics, healthcare, transportation and criminology. Highlighting the Importance of Big Data Management and Analysis for Various Applications will provide the reader with an understanding of how data management and analysis are adapted to these applications. This book will appeal to researchers and professionals in the field.
This book investigates the impact of production input factors on the market, consumer and producer energy demand characteristics in 30 industrial sectors for South Korea over the period 1980-2009, and for Japan over the period 1973-2006, with special emphasis placed on the effects of ICT investment on the demand for energy. A dynamic factor demand model is developed, accounting for the adjustment costs that are defined in terms of forgone output from current production. It addresses four key aspects of production and energy demand in manufacturing: first, it establishes the various relationships between different factors of production. Second, it investigates whether the energy demand in the industrial sectors in South Korea would be decreased or increased by substituting/complementing with other input factors such as ICT capital and labor. Third, it looks at sources of growth in the industrial sectors through decomposing the Divisia index based total factor productivity (TFP). Finally it provides appropriate policy recommendations based on these findings. The results of this study may provide industrial sectors' stakeholders and environmental and industrial policy makers with a flexible model that has the capacity to assess outcomes of various policies under certain scenarios. The factor demand methodology described in this book is very advanced and up-to-date. It can be used when teaching advanced graduate courses and in empirically advanced research. Therefore, it is highly relevant in both teaching as a main or supplementary text and in particular as a reference handbook in conducting empirical research. The focus on ICT effects on energy use makes this book an important addition to the existing literature on industrial development.
This monograph illustrates important notions in security reductions and essential techniques in security reductions for group-based cryptosystems. Using digital signatures and encryption as examples, the authors explain how to program correct security reductions for those cryptographic primitives. Various schemes are selected and re-proven in this book to demonstrate and exemplify correct security reductions. This book is suitable for researchers and graduate students engaged with public-key cryptography.
This book presents a collection of representative and novel work in the field of data mining, knowledge discovery, clustering and classification, based on expanded and reworked versions of a selection of the best papers originally presented in French at the EGC 2014 and EGC 2015 conferences held in Rennes (France) in January 2014 and Luxembourg in January 2015. The book is in three parts: The first four chapters discuss optimization considerations in data mining. The second part explores specific quality measures, dissimilarities and ultrametrics. The final chapters focus on semantics, ontologies and social networks. Written for PhD and MSc students, as well as researchers working in the field, it addresses both theoretical and practical aspects of knowledge discovery and management.
This book presents the latest on the theoretical approach of the contemporary issues evolved in strategic marketing and the integration of theory and practice. It seeks to make advancements in the discipline by promoting strategic research and innovative activities in marketing. The book highlights the use of data analytics, intelligence and knowledge-based systems in this area. In the era of knowledge-based economy, marketing has a lot to gain from collecting and analyzing data associated with customers, business processes, market economics or even data related to social activities. The contributed chapters are concerned with using modern qualitative and quantitative techniques based on information technology used to manage and analyze business data, to discover hidden knowledge and to introduce intelligence into marketing processes. This allows for a focus on innovative applications in all aspects of marketing, of computerized technologies related to data analytics, predictive analytics and modeling, business intelligence and knowledge engineering, in order to demonstrate new ways of uncovering hidden knowledge and supporting marketing decisions with evidence-based intelligent tools. Among the topics covered include innovative tourism marketing strategies, marketing communications in small and medium-sized enterprises (SMEs), the use of business modeling, as well as reflecting on the marketing trends and outlook for all transportation industry segments. The papers in this proceedings has been written by scientists, researchers, practitioners and students that demonstrate a special orientation in strategic marketing, all of whom aspire to be ahead of the curve based on the pillars of innovation. This proceedings volume compiles their contributions to the field, highlighting the exchange of insights on strategic issues in the science of innovation marketing.
This book shows how to model selected communication scenarios using game theory. The book helps researchers specifically dealing with scenarios motivated by the increasing use of the Internet of Things (IoT) and 5G Communications by using game theory to approach the study of such challenging scenarios. The author explains how game theory acts as a mathematical tool that models decision making in terms of strategies and mechanisms that can result in optimal payoffs for a number of interacting entities, offering often antagonistic behaviors. The book explores new technologies in terms of design, development and management from a theoretical perspective, using game theory to analyze strategic situations and demonstrate profitable behaviors of the cooperative entities. The book identifies and explores several significant applications/uses/situations that arise from the vast deployment of the IoT. The presentation of the technological scenarios is followed in each of the first four chapters by a step-by-step theoretical model often followed by equilibrium proof, and numerical simulation results, that are explained in a tutorial-like manner. The four chapters tackle challenging IoT and 5G related issues, including: new security threats that IoT brings, e.g. botnets, ad hoc vehicular networks and the need for trust in vehicular communications, content repetition by offloading traffic onto mobile users, as well as issues due to new wearable devices that enable data collection to become more intrusive.
"Applications, 2nd Edition" focuses on moving object management, from the location management perspective to determining how constantly changing locations affect the traditional database and data mining technology. The book specifically describes the topics of moving objects modeling and location tracking, indexing and querying, clustering, location uncertainty, traffic-aware navigation and privacy issues, as well as the application to intelligent transportation systems. Through the book, the readers will be made familiar with the cutting-edge technologies in moving object management that can be effectively applied in LBS and transportation contexts. The second edition of this book significantly expands the coverage of the latest research on location privacy, traffic-aware navigation and uncertainty. The book has also been reorganized, with nearly all chapters rewritten, and several new chapters have been added to address the latest topics on moving objects management. Xiaofeng Meng is a professor at the School of Information, Renmin University of China; Zhiming Ding is a professor at the Institute of Software, Chinese Academy of Sciences (ISCAS); Jiajie Xu is an assistant professor at the ISCAS.
This book not only discusses the important topics in the area of machine learning and combinatorial optimization, it also combines them into one. This was decisive for choosing the material to be included in the book and determining its order of presentation. Decision trees are a popular method of classification as well as of knowledge representation. At the same time, they are easy to implement as the building blocks of an ensemble of classifiers. Admittedly, however, the task of constructing a near-optimal decision tree is a very complex process. The good results typically achieved by the ant colony optimization algorithms when dealing with combinatorial optimization problems suggest the possibility of also using that approach for effectively constructing decision trees. The underlying rationale is that both problem classes can be presented as graphs. This fact leads to option of considering a larger spectrum of solutions than those based on the heuristic. Moreover, ant colony optimization algorithms can be used to advantage when building ensembles of classifiers. This book is a combination of a research monograph and a textbook. It can be used in graduate courses, but is also of interest to researchers, both specialists in machine learning and those applying machine learning methods to cope with problems from any field of R&D.
Data analysis forms the basis of many modes of research ranging from scientific discoveries to governmental findings. With the advent of machine intelligence and neural networks, extracting and modeling, approaching data has been unimpeachably altered. These changes, seemingly small, affect the way societies organize themselves, deliver services, or interact with each other. Predictive Analysis on Large Data for Actionable Knowledge: Emerging Research and Opportunities provides emerging information on extraction and prediction patterns in data mining along with knowledge discovery. While highlighting the current issues in data extraction, readers will learn new methodologies comprising of different algorithms that automate the multidimensional schema that remove the manual processes. This book is a vital resource for researchers, academics, and those seeking new information on data mining techniques and trends.
This open access book is a step-by-step introduction on how shell scripting can help solve many of the data processing tasks that Health and Life specialists face everyday with minimal software dependencies. The examples presented in the book show how simple command line tools can be used and combined to retrieve data and text from web resources, to filter and mine literature, and to explore the semantics encoded in biomedical ontologies. To store data this book relies on open standard text file formats, such as TSV, CSV, XML, and OWL, that can be open by any text editor or spreadsheet application. The first two chapters, Introduction and Resources, provide a brief introduction to the shell scripting and describe popular data resources in Health and Life Sciences. The third chapter, Data Retrieval, starts by introducing a common data processing task that involves multiple data resources. Then, this chapter explains how to automate each step of that task by introducing the required commands line tools one by one. The fourth chapter, Text Processing, shows how to filter and analyze text by using simple string matching techniques and regular expressions. The last chapter, Semantic Processing, shows how XPath queries and shell scripting is able to process complex data, such as the graphs used to specify ontologies. Besides being almost immutable for more than four decades and being available in most of our personal computers, shell scripting is relatively easy to learn by Health and Life specialists as a sequence of independent commands. Comprehending them is like conducting a new laboratory protocol by testing and understanding its procedural steps and variables, and combining their intermediate results. Thus, this book is particularly relevant to Health and Life specialists or students that want to easily learn how to process data and text, and which in return may facilitate and inspire them to acquire deeper bioinformatics skills in the future.
This book presents the first paradigm of social multimedia computing completely from the user perspective. Different from traditional multimedia and web multimedia computing which are content-centric, social multimedia computing rises under the participatory Web2.0 and is essentially user-centric. The goal of this book is to emphasize the user factor in facilitating effective solutions towards both multimedia content analysis, user modeling and customized user services. Advanced topics like cross-network social multimedia computing are also introduced as extensions and potential directions along this research line.
This book presents the latest research ideas and topics on how to enhance current database systems, improve information storage, refine existing database models, and develop advanced applications. It provides insights into important developments in the field of database and database management. With emphasis on theoretical issues regarding databases and database management, the book describes the capabilities and features of new technologies and methodologies, and addresses the needs of database researchers and practitioners. *Note: This book is part of a new series entitled "Advanced Topics in Database Research." This book is Volume Three within this series (Vol. III, 2004). |
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