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The present work covers the latest developments and discoveries related to information reuse and integration in academia and industrial settings. The need for dealing with the large volumes of data being produced and stored in the last decades and the numerous systems developed to deal with these is increasingly necessary. Not all these developments could have been achieved without the investing large amounts of resources. Over time, new data sources evolve and data integration continues to be an essential and vital requirement. Furthermore, systems and products need to be revised to adapt new technologies and needs. Instead of building these from scratch, researchers in the academia and industry have realized the benefits of reusing existing components that have been well tested. While this trend avoids reinventing the wheel, it comes at the cost of finding the optimum set of existing components to be utilized and how they should be integrated together and with the new non-existing components which are to be developed. These nontrivial tasks have led to challenging research problems in the academia and industry. These issues are addressed in this book, which is intended to be a unique resource for researchers, developers and practitioners.
Data mining. --- Information retrieval. --- Data retrieval --- Data storage --- Discovery, Information --- Information discovery --- Information storage and retrieval --- Retrieval of information --- Documentation --- Information science --- Information storage and retrieval systems --- Algorithmic knowledge discovery --- Factual data analysis --- KDD (Information retrieval) --- Knowledge discovery in data --- Knowledge discovery in databases --- Mining, Data --- Database searching --- Information systems. --- Information Systems and Communication Service. --- Organizational Studies, Economic Sociology. --- Computers. --- Economic sociology. --- Economic sociology --- Economics --- Socio-economics --- Socioeconomics --- Sociology of economics --- Sociology --- Automatic computers --- Automatic data processors --- Computer hardware --- Computing machines (Computers) --- Electronic brains --- Electronic calculating-machines --- Electronic computers --- Hardware, Computer --- Computer systems --- Cybernetics --- Machine theory --- Calculators --- Cyberspace --- Social aspects --- Data integration (Computer science)
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Crime, terrorism and security are in the forefront of current societal concerns. This edited volume presents research based on social network techniques showing how data from crime and terror networks can be analyzed and how information can be extracted. The topics covered include crime data mining and visualization; organized crime detection; crime network visualization; computational criminology; aspects of terror network analyses and threat prediction including cyberterrorism and the related area of dark web; privacy issues in social networks; security informatics; graph algorithms for social networks; general aspects of social networks such as pattern and anomaly detection; community discovery; link analysis and spatio-temporal network mining. These topics will be of interest to researchers and practitioners in the general area of security informatics. The volume will also serve as a general reference for readers that would want to become familiar with current research in the fast growing field of cybersecurity.
Computer networks -- Security measures. --- Data mining. --- Online social networks. --- Terrorism --- Prevention. --- Anti-terrorism --- Antiterrorism --- Counter-terrorism --- Counterterrorism --- Algorithmic knowledge discovery --- Factual data analysis --- KDD (Information retrieval) --- Knowledge discovery in data --- Knowledge discovery in databases --- Mining, Data --- Physics. --- System safety. --- Complexity, Computational. --- Economic theory. --- Security Science and Technology. --- Data Mining and Knowledge Discovery. --- Criminology and Criminal Justice, general. --- Economic Theory/Quantitative Economics/Mathematical Methods. --- Complexity. --- Database searching --- Economic theory --- Political economy --- Social sciences --- Economic man --- Complexity, Computational --- Electronic data processing --- Machine theory --- Safety, System --- Safety of systems --- Systems safety --- Accidents --- Industrial safety --- Systems engineering --- Natural philosophy --- Philosophy, Natural --- Physical sciences --- Dynamics --- Prevention --- Criminology. --- Engineering. --- Crime --- Criminals --- Construction --- Industrial arts --- Technology --- Study and teaching --- Computational complexity.
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The book covers tools in the study of online social networks such as machine learning techniques, clustering, and deep learning. A variety of theoretical aspects, application domains, and case studies for analyzing social network data are covered. The aim is to provide new perspectives on utilizing machine learning and related scientific methods and techniques for social network analysis. Machine Learning Techniques for Online Social Networks will appeal to researchers and students in these fields. .
Social sciences. --- Social media. --- Data mining. --- Artificial intelligence. --- Social Sciences. --- Computational Social Sciences. --- Data Mining and Knowledge Discovery. --- Social Media. --- Artificial Intelligence (incl. Robotics). --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Algorithmic knowledge discovery --- Factual data analysis --- KDD (Information retrieval) --- Knowledge discovery in data --- Knowledge discovery in databases --- Mining, Data --- Database searching --- User-generated media --- Communication --- User-generated content --- Behavioral sciences --- Human sciences --- Sciences, Social --- Social science --- Social studies --- Civilization --- Online social networks --- Economic aspects. --- Electronic social networks --- Social networking Web sites --- Social media --- Social networks --- Sociotechnical systems --- Web sites --- Social sciences—Data processing. --- Social sciences—Computer programs. --- Artificial Intelligence.
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The book covers tools in the study of online social networks such as machine learning techniques, clustering, and deep learning. A variety of theoretical aspects, application domains, and case studies for analyzing social network data are covered. The aim is to provide new perspectives on utilizing machine learning and related scientific methods and techniques for social network analysis. Machine Learning Techniques for Online Social Networks will appeal to researchers and students in these fields. .
Sociology --- Social sciences --- Mass communications --- Computer architecture. Operating systems --- Information systems --- Artificial intelligence. Robotics. Simulation. Graphics --- Computer. Automation --- datamining --- sociale media --- machine learning --- deep learning --- sociale wetenschappen --- computerprogramma's --- KI (kunstmatige intelligentie) --- data acquisition --- gegevensverwerking
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Social network analysis increasingly bridges the discovery of patterns in diverse areas of study as more data becomes available and complex. Yet the construction of huge networks from large data often requires entirely different approaches for analysis including; graph theory, statistics, machine learning and data mining. This work covers frontier studies on social network analysis and mining from different perspectives such as social network sites, financial data, e-mails, forums, academic research funds, XML technology, blog content, community detection and clique finding, prediction of user’s- behavior, privacy in social network analysis, mobility from spatio-temporal point of view, agent technology and political parties in parliament. These topics will be of interest to researchers and practitioners from different disciplines including, but not limited to, social sciences and engineering.
Computer science. --- Data mining. --- Physics. --- Computational intelligence. --- Computer Science. --- Data Mining and Knowledge Discovery. --- Computational Intelligence. --- Complex Networks. --- Intelligence, Computational --- Artificial intelligence --- Soft computing --- Natural philosophy --- Philosophy, Natural --- Physical sciences --- Dynamics --- Algorithmic knowledge discovery --- Factual data analysis --- KDD (Information retrieval) --- Knowledge discovery in data --- Knowledge discovery in databases --- Mining, Data --- Database searching --- Informatics --- Science --- Online social networks --- Data mining --- Design. --- Data processing. --- Electronic social networks --- Social networking Web sites --- Social media --- Social networks --- Sociotechnical systems --- Web sites --- Engineering. --- Applications of Graph Theory and Complex Networks. --- Construction --- Industrial arts --- Technology --- Virtual communities
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The present text aims at helping the reader to maximize the reuse of information. Topics covered include tools and services for creating simple, rich, and reusable knowledge representations to explore strategies for integrating this knowledge into legacy systems. The reuse and integration are essential concepts that must be enforced to avoid duplicating the effort and reinventing the wheel each time in the same field. This problem is investigated from different perspectives. in organizations, high volumes of data from different sources form a big threat for filtering out the information for effective decision making. the reader will be informed of the most recent advances in information reuse and integration.
Data integration (Computer science). --- Data mining. --- Information retrieval. --- Engineering & Applied Sciences --- Computer Science --- Information technology. --- Knowledge management. --- Management of knowledge assets --- IT (Information technology) --- Computer science. --- Information storage and retrieval. --- Computer Science. --- Information Storage and Retrieval. --- Data Mining and Knowledge Discovery. --- Management --- Information technology --- Intellectual capital --- Organizational learning --- Technology --- Telematics --- Information superhighway --- Knowledge management --- Information storage and retrieva. --- Algorithmic knowledge discovery --- Factual data analysis --- KDD (Information retrieval) --- Knowledge discovery in data --- Knowledge discovery in databases --- Mining, Data --- Database searching --- Information storage and retrieval systems. --- Automatic data storage --- Automatic information retrieval --- Automation in documentation --- Computer-based information systems --- Data processing systems --- Data storage and retrieval systems --- Discovery systems, Information --- Information discovery systems --- Information processing systems --- Information retrieval systems --- Machine data storage and retrieval --- Mechanized information storage and retrieval systems --- Computer systems --- Electronic information resources --- Data libraries --- Digital libraries --- Information organization --- Information retrieval
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This book addresses the challenges of social network and social media analysis in terms of prediction and inference. The chapters collected here tackle these issues by proposing new analysis methods and by examining mining methods for the vast amount of social content produced. Social Networks (SNs) have become an integral part of our lives; they are used for leisure, business, government, medical, educational purposes and have attracted billions of users. The challenges that stem from this wide adoption of SNs are vast. These include generating realistic social network topologies, awareness of user activities, topic and trend generation, estimation of user attributes from their social content, and behavior detection. This text has applications to widely used platforms such as Twitter and Facebook and appeals to students, researchers, and professionals in the field.
Computer science. --- Data mining. --- User interfaces (Computer systems). --- Computers and civilization. --- Computer Science. --- Data Mining and Knowledge Discovery. --- Applications of Graph Theory and Complex Networks. --- Computers and Society. --- User Interfaces and Human Computer Interaction. --- Social prediction. --- Social networks. --- Social media. --- User-generated media --- Networking, Social --- Networks, Social --- Social networking --- Social support systems --- Support systems, Social --- Prediction, Social --- Social forecasting --- Sociological prediction --- Civilization and computers --- Civilization --- Interfaces, User (Computer systems) --- Human-machine systems --- Human-computer interaction --- Algorithmic knowledge discovery --- Factual data analysis --- KDD (Information retrieval) --- Knowledge discovery in data --- Knowledge discovery in databases --- Mining, Data --- Database searching --- Informatics --- Science --- Communication --- User-generated content --- Interpersonal relations --- Cliques (Sociology) --- Microblogs --- Forecasting --- Sociology --- Social indicators --- Statistical methods --- Physics. --- Natural philosophy --- Philosophy, Natural --- Physical sciences --- Dynamics
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This book focuses on recent technical advancements and state-of-the art technologies for analyzing characteristic features and probabilistic modelling of complex social networks and decentralized online network architectures. Such research results in applications related to surveillance and privacy, fraud analysis, cyber forensics, propaganda campaigns, as well as for online social networks such as Facebook. The text illustrates the benefits of using advanced social network analysis methods through application case studies based on practical test results from synthetic and real-world data. This book will appeal to researchers and students working in these areas. .
Social sciences—Data processing. --- Social sciences—Computer programs. --- Data mining. --- Social media. --- Social sciences --- Computational Social Sciences. --- Data Mining and Knowledge Discovery. --- Social Media. --- Computer Appl. in Social and Behavioral Sciences. --- User-generated media --- Communication --- User-generated content --- Algorithmic knowledge discovery --- Factual data analysis --- KDD (Information retrieval) --- Knowledge discovery in data --- Knowledge discovery in databases --- Mining, Data --- Database searching --- Data processing. --- Application software. --- Application computer programs --- Application computer software --- Applications software --- Apps (Computer software) --- Computer software
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Information systems --- Computer. Automation --- IR (information retrieval) --- database management
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