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).

This book is intended to spark a discourse on, and contribute to finding a clear consensus in, the debate between conceptualizing a knowledge strategy and planning a knowledge strategy. It explores the complex relationship between the notions of knowledge and strategy in the business context, one that is of practical importance to companies. After reviewing the extant literature, the book shows how the concept of knowledge strategies can be seen as a new perspective for exploring business strategies. It proposes a new approach that clarifies how planned and emergent knowledge strategies allow companies to make projections into the uncertain and unpredictable future that dominates today's economy.

The rapid increase in computing power and communication speed, coupled with computer storage facilities availability, has led to a new age of multimedia app- cations. Multimedia is practically everywhere and all around us we can feel its presence in almost all applications ranging from online video databases, IPTV, - teractive multimedia and more recently in multimedia based social interaction. These new growing applications require high-quality data storage, easy access to multimedia content and reliable delivery. Moving ever closer to commercial - ployment also aroused a higher awareness of security and intellectual property management issues. All the aforementioned requirements resulted in higher demands on various - eas of research (signal processing, image/video processing and analysis, com- nication protocols, content search, watermarking, etc.). This book covers the most prominent research issues in multimedia and is divided into four main sections: i) content based retrieval, ii) storage and remote access, iii) watermarking and co- right protection and iv) multimedia applications. Chapter 1 of the first section presents an analysis on how color is used and why is it crucial in nowadays multimedia applications. In chapter 2 the authors give an overview of the advances in video abstraction for fast content browsing, transm- sion, retrieval and skimming in large video databases and chapter 3 extends the discussion on video summarization even further. Content retrieval problem is tackled in chapter 4 by describing a novel method for producing meaningful s- ments suitable for MPEG-7 description based on binary partition trees (BPTs).

Grids, P2P and Services Computing, the 12th volume of the CoreGRID series, is based on the CoreGrid ERCIM Working Group Workshop on Grids, P2P and Service Computing in Conjunction with EuroPar 2009. The workshop will take place August 24th, 2009 in Delft, The Netherlands. Grids, P2P and Services Computing, an edited volume contributed by well-established researchers worldwide, will focus on solving research challenges for Grid and P2P technologies. Topics of interest include: Service Level Agreement, Data & Knowledge Management, Scheduling, Trust and Security, Network Monitoring and more. Grids are a crucial enabling technology for scientific and industrial development. This book also includes new challenges related to service-oriented infrastructures. Grids, P2P and Services Computing is designed for a professional audience composed of researchers and practitioners within the Grid community industry. This volume is also suitable for advanced-level students in computer science.

This book explores a society currently being transformed by the influence of advanced information technology, and provides insights into the main technological and human issues and a holistic approach to inclusion, security, safety and, last but not least, privacy and freedom of expression. Its main aim is to bridge the gap between technological solutions, their successful implementation, and the fruitful utilization of the main set of e-Services offered by governments, private institutions, and commercial companies. Today, various parameters actively influence e-Services' success or failure: cultural aspects, organisational issues, bureaucracy and workflow, infrastructure and technology in general, user habits, literacy, capacity or merely interaction design. The purpose of this book is to help in outlining and understanding a realistic scenario of what we can term e-Citizenry. It identifies today's citizen, who is surrounded by an abundance of digital services, as an "e-Citizen" and explores the transition from their traditional role and behaviour to new ones. The respective chapters presented here will lay the foundation of the technological and social environment in which this societal transition takes place. With its balanced humanistic and technological approach, the book mainly targets public authorities, decision-makers, stakeholders, solution developers, and graduate students.

This book discusses the psychological traits associated with drug consumption through the statistical analysis of a new database with information on 1885 respondents and use of 18 drugs. After reviewing published works on the psychological profiles of drug users and describing the data mining and machine learning methods used, it demonstrates that the personality traits (five factor model, impulsivity, and sensation seeking) together with simple demographic data make it possible to predict the risk of consumption of individual drugs with a sensitivity and specificity above 70% for most drugs. It also analyzes the correlations of use of different substances and describes the groups of drugs with correlated use, identifying significant differences in personality profiles for users of different drugs. The book is intended for advanced undergraduates and first-year PhD students, as well as researchers and practitioners. Although no previous knowledge of machine learning, advanced data mining concepts or modern psychology of personality is assumed, familiarity with basic statistics and some experience in the use of probabilities would be helpful. For a more detailed introduction to statistical methods, the book provides recommendations for undergraduate textbooks.

The development of business intelligence has enhanced the visualization of data to inform and facilitate business management and strategizing. By implementing effective data-driven techniques, this allows for advance reporting tools to cater to company-specific issues and challenges. The Handbook of Research on Advanced Data Mining Techniques and Applications for Business Intelligence is a key resource on the latest advancements in business applications and the use of mining software solutions to achieve optimal decision-making and risk management results. Highlighting innovative studies on data warehousing, business activity monitoring, and text mining, this publication is an ideal reference source for research scholars, management faculty, and practitioners.

This book presents recent machine learning paradigms and advances in learning analytics, an emerging research discipline concerned with the collection, advanced processing, and extraction of useful information from both educators' and learners' data with the goal of improving education and learning systems. In this context, internationally respected researchers present various aspects of learning analytics and selected application areas, including: * Using learning analytics to measure student engagement, to quantify the learning experience and to facilitate self-regulation; * Using learning analytics to predict student performance; * Using learning analytics to create learning materials and educational courses; and * Using learning analytics as a tool to support learners and educators in synchronous and asynchronous eLearning. The book offers a valuable asset for professors, researchers, scientists, engineers and students of all disciplines. Extensive bibliographies at the end of each chapter guide readers to probe further into their application areas of interest.

This book is the proceedings of the 3rd World Conference on Soft Computing (WCSC), which was held in San Antonio, TX, USA, on December 16-18, 2013. It presents start-of-the-art theory and applications of soft computing together with an in-depth discussion of current and future challenges in the field, providing readers with a 360 degree view on soft computing. Topics range from fuzzy sets, to fuzzy logic, fuzzy mathematics, neuro-fuzzy systems, fuzzy control, decision making in fuzzy environments, image processing and many more. The book is dedicated to Lotfi A. Zadeh, a renowned specialist in signal analysis and control systems research who proposed the idea of fuzzy sets, in which an element may have a partial membership, in the early 1960s, followed by the idea of fuzzy logic, in which a statement can be true only to a certain degree, with degrees described by numbers in the interval [0,1]. The performance of fuzzy systems can often be improved with the help of optimization techniques, e.g. evolutionary computation, and by endowing the corresponding system with the ability to learn, e.g. by combining fuzzy systems with neural networks. The resulting "consortium" of fuzzy, evolutionary, and neural techniques is known as soft computing and is the main focus of this book.

An ontology is a formal description of concepts and relationships that can exist for a community of human and/or machine agents. The notion of ontologies is crucial for the purpose of enabling knowledge sharing and reuse. The Handbook on Ontologies provides a comprehensive overview of the current status and future prospectives of the field of ontologies considering ontology languages, ontology engineering methods, example ontologies, infrastructures and technologies for ontologies, and how to bring this all into ontology-based infrastructures and applications that are among the best of their kind. The field of ontologies has tremendously developed and grown in the five years since the first edition of the "Handbook on Ontologies." Therefore, its revision includes 21 completely new chapters as well as a major re-working of 15 chapters transferred to this second edition.

This book offers an introduction to artificial adaptive systems and a general model of the relationships between the data and algorithms used to analyze them. It subsequently describes artificial neural networks as a subclass of artificial adaptive systems, and reports on the backpropagation algorithm, while also identifying an important connection between supervised and unsupervised artificial neural networks. The book's primary focus is on the auto contractive map, an unsupervised artificial neural network employing a fixed point method versus traditional energy minimization. This is a powerful tool for understanding, associating and transforming data, as demonstrated in the numerous examples presented here. A supervised version of the auto contracting map is also introduced as an outstanding method for recognizing digits and defects. In closing, the book walks the readers through the theory and examples of how the auto contracting map can be used in conjunction with another artificial neural network, the "spin-net," as a dynamic form of auto-associative memory.

This volume summarizes the author's work on social information seeking (SIS), and at the same time serves as an introduction to the topic. Sometimes also referred to as social search or social information retrieval, this is a relatively new area of study concerned with the seeking and acquiring of information from social spaces on the Internet. It involves studying situations, motivations, and methods involved in seeking and sharing of information in participatory online social sites, such as Yahoo! Answers, WikiAnswers, and Twitter, as well as building systems for supporting such activities. The first part of the book introduces various foundational concepts, including information seeking, social media, and social networking. As such it provides the necessary basis to then discuss how those aspects could intertwine in different ways to create methods, tools, and opportunities for supporting and leveraging SIS. Next, Part II discusses the social dimension and primarily examines the online question-answering activity. Part III then emphasizes the collaborative aspect of information seeking, and examines what happens when social and collaborative dimensions are considered together. Lastly, Part IV provides a synthesis by consolidating methods, systems, and evaluation techniques related to social and collaborative information seeking. The book is completed by a list of challenges and opportunities for both theoretical and practical SIS work. The book is intended mainly for researchers and graduate students looking for an introduction to this new field, as well as developers and system designers interested in building interactive information retrieval systems or social/community-driven interfaces.

This monograph provides a comprehensive research review of intelligent techniques for personalisation of e-learning systems. Special emphasis is given to intelligent tutoring systems as a particular class of e-learning systems, which support and improve the learning and teaching of domain-specific knowledge. A new approach to perform effective personalization based on Semantic web technologies achieved in a tutoring system is presented. This approach incorporates a recommender system based on collaborative tagging techniques that adapts to the interests and level of students' knowledge. These innovations are important contributions of this monograph. Theoretical models and techniques are illustrated on a real personalised tutoring system for teaching Java programming language. The monograph is directed to, students and researchers interested in the e-learning and personalization techniques.

This book deals with timing attacks on cryptographic ciphers. It describes and analyzes various unintended covert timing channels that are formed when ciphers are executed in microprocessors. The book considers modern superscalar microprocessors which are enabled with features such as multi-threaded, pipelined, parallel, speculative, and out-of order execution. Various timing attack algorithms are described and analyzed for both block ciphers as well as public-key ciphers. The interplay between the cipher implementation, the system architecture, and the attack's success is analyzed. Further hardware and software countermeasures are discussed with the aim of illustrating methods to build systems that can protect against these attacks.

Focuses on the process by which manually crafting interactive, hypertextual maps clarifies one's own understanding, communicates it to others, and enables collective intelligence. The authors see mapping software as visual tools for reading and writing in a networked age. In an information ocean, the challenge is to find meaningful patterns around which we can weave plausible narratives. Maps of concepts, discussions and arguments make the connections between ideas tangible - and critically, disputable. With 22 chapters from leading researchers and practitioners (5 of them new for this edition), the reader will find the current state-of-the-art in the field. Part 1 focuses on knowledge maps for learning and teaching in schools and universities, before Part 2 turns to knowledge maps for information analysis and knowledge management in professional communities, but with many cross-cutting themes: * reflective practitioners documenting the most effective ways to map * conceptual frameworks for evaluating representations * real world case studies showing added value for professionals * more experimental case studies from research and education * visual languages, many of which work on both paper and with software * knowledge cartography software, much of it freely available and open source * visit the companion website for extra resources: books.kmi.open.ac.uk/knowledge-cartography Knowledge Cartography will be of interest to learners, educators, and researchers in all disciplines, as well as policy analysts, scenario planners, knowledge managers and team facilitators. Practitioners will find new perspectives and tools to expand their repertoire, while researchers will find rich enough conceptual grounding for further scholarship.

Through interaction with other databases such as social media, geographic information systems have the ability to build and obtain not only statistics defined on the flows of people, things, and information but also on perceptions, impressions, and opinions about specific places, territories, and landscapes. It is thus necessary to systematize, integrate, and coordinate the various sources of data (especially open data) to allow more appropriate and complete analysis, descriptions, and elaborations. Spatial Planning in the Big Data Revolution is a critical scholarly resource that aims to bring together different methodologies that combine the potential of large data analysis with GIS applications in dedicated tools specifically for territorial, social, economic, environmental, transport, energy, real estate, and landscape evaluation. Additionally, the book addresses a number of fundamental objectives including the application of big data analysis in supporting territorial analysis, validating crowdsourcing and crowdmapping techniques, and disseminating information and community involvement. Urban planners, architects, researchers, academicians, professionals, and practitioners in such fields as computer science, data science, and business intelligence will benefit most from the research contained within this publication.