This book constitutes the proceedings of the 16th Russian Conference on Artificial Intelligence, RCAI 2018, Moscow, Russia, in September 2018. The 22 full papers presented along with 4 short papers in this volume were carefully reviewed and selected from 75 submissions. The conference deals with a wide range of topics, including data mining and knowledge discovery, text mining, reasoning, decision making, natural language processing, vision, intelligent robotics, multi-agent systems, machine learning, ontology engineering.

The three-volume set LNCS 101164, 11165, and 11166 constitutes the refereed proceedings of the 19th Pacific-Rim Conference on Multimedia, PCM 2018, held in Hefei, China, in September 2018. The 209 regular papers presented together with 20 special session papers were carefully reviewed and selected from 452 submissions. The papers cover topics such as: multimedia content analysis; multimedia signal processing and communications; and multimedia applications and services.

This two-volume set (CCIS 873 and CCIS 874) constitutes the thoroughly refereed proceedings of the 9th International Symposium, ISICA 2017, held in Guangzhou, China, in November 2017.The 101 full papers presented in both volumes were carefully reviewed and selected from 181 submissions. This first volume is organized in topical sections on neural networks and statistical learning: neural architecture search, transfer of knowledge; evolutionary multi-objective and dynamic optimization: optimal control and design, hybrid methods; data mining: association rule learning, data management platforms; Cloud computing and multiagent systems: service models, Cloud engineering; everywhere connectivity: IoT solutions, wireless sensor networks.

This handbook offers comprehensive coverage of recent advancements in Big Data technologies and related paradigms. Chapters are authored by international leading experts in the field, and have been reviewed and revised for maximum reader value. The volume consists of twenty-five chapters organized into four main parts. Part one covers the fundamental concepts of Big Data technologies including data curation mechanisms, data models, storage models, programming models and programming platforms. It also dives into the details of implementing Big SQL query engines and big stream processing systems. Part Two focuses on the semantic aspects of Big Data management including data integration and exploratory ad hoc analysis in addition to structured querying and pattern matching techniques. Part Three presents a comprehensive overview of large scale graph processing. It covers the most recent research in large scale graph processing platforms, introducing several scalable graph querying and mining mechanisms in domains such as social networks. Part Four details novel applications that have been made possible by the rapid emergence of Big Data technologies such as Internet-of-Things (IOT), Cognitive Computing and SCADA Systems. All parts of the book discuss open research problems, including potential opportunities, that have arisen from the rapid progress of Big Data technologies and the associated increasing requirements of application domains. Designed for researchers, IT professionals and graduate students, this book is a timely contribution to the growing Big Data field. Big Data has been recognized as one of leading emerging technologies that will have a major contribution and impact on the various fields of science and varies aspect of the human society over the coming decades. Therefore, the content in this book will be an essential tool to help readers understand the development and future of the field.

This two-volume set (CCIS 873 and CCIS 874) constitutes the thoroughly refereed proceedings of the 9th International Symposium, ISICA 2017, held in Guangzhou, China, in November 2017. The 101 full papers presented in both volumes were carefully reviewed and selected from 181 submissions. This second volume is organized in topical sections on swarm intelligence: cooperative Search, swarm optimization; complex systems modeling: system dynamic, multimedia simulation; intelligent information systems: information retrieval, e-commerce platforms; artificial intelligence and robotics: query optimization, intelligent engineering; virtualization: motion-based tracking, image recognition.

This book constitutes the refereed proceedings of the 18th International Conference on Artificial Intelligence: Methodology, Systems, and Applications, AIMSA 2018, held in Varna, Bulgaria, in September 2018. The 22 revised full papers and 7 poster papers presented were carefully reviewed and selected from 72 submissions. They cover a wide range of topics in AI: from machine learning to natural language systems, from information extraction to text mining, from knowledge representation to soft computing; from theoretical issues to real-world applications.

This book constitutes the refereed proceedings of the International Conference on Privacy in Statistical Databases, PSD 2018, held in Valencia, Spain, in September 2018 under the sponsorship of the UNESCO Chair in Data Privacy. The 23 revised full papers presented were carefully reviewed and selected from 42 submissions. The papers are organized into the following topics: tabular data protection; synthetic data; microdata and big data masking; record linkage; and spatial and mobility data. Chapter "SwapMob: Swapping Trajectories for Mobility Anonymization" is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.

This book presents statistical processes for health care delivery and covers new ideas, methods and technologies used to improve health care organizations. It gathers the proceedings of the Third International Conference on Health Care Systems Engineering (HCSE 2017), which took place in Florence, Italy from May 29 to 31, 2017. The Conference provided a timely opportunity to address operations research and operations management issues in health care delivery systems. Scientists and practitioners discussed new ideas, methods and technologies for improving the operations of health care systems, developed in close collaborations with clinicians. The topics cover a broad spectrum of concrete problems that pose challenges for researchers and practitioners alike: hospital drug logistics, operating theatre management, home care services, modeling, simulation, process mining and data mining in patient care and health care organizations.

This book focuses on the data mining, systems biology, and bioinformatics computational methods that can be used to summarize biological networks. Specifically, it discusses an array of techniques related to biological network clustering, network summarization, and differential network analysis which enable readers to uncover the functional and topological organization hidden in a large biological network. The authors also examine crucial open research problems in this arena. Academics, researchers, and advanced-level students will find this book to be a comprehensive and exceptional resource for understanding computational techniques and their applications for a summary of biological networks.

This work provides an innovative look at the use of open data for extracting information to detect and prevent crime, and also explores the link between terrorism and organized crime. In counter-terrorism and other forms of crime prevention, foresight about potential threats is vitally important and this information is increasingly available via electronic data sources such as social media communications. However, the amount and quality of these sources is varied, and researchers and law enforcement need guidance about when and how to extract useful information from them. The emergence of these crime threats, such as communication between organized crime networks and radicalization towards terrorism, is driven by a combination of political, economic, social, technological, legal and environmental factors. The contributions to this volume represent a major step by researchers to systematically collect, filter, interpret, and use the information available. For the purposes of this book, the only data sources used are publicly available sources which can be accessed legally and ethically. This work will be of interest to researchers in criminology and criminal justice, particularly in police science, organized crime, counter-terrorism and crime science. It will also be of interest to those in related fields such as applications of computer science and data mining, public policy, and business intelligence.

This book presents a multi-disciplinary investigation into extortion rackets with a particular focus on the structures of criminal organisations and their collapse, societal processes in which extortion rackets strive and fail and the impacts of bottom-up and top-down ways of fighting extortion racketeering. Through integrating a range of disciplines and methods the book provides an extensive case study of empirically based computational social science. It is based on a wealth of qualitative data regarding multiple extortion rackets, such as the Sicilian Mafia, an international money laundering organisation and a predatory extortion case in Germany. Computational methods are used for data analysis, to help in operationalising data for use in agent-based models and to explore structures and dynamics of extortion racketeering through simulations. In addition to textual data sources, stakeholders and experts are extensively involved, providing narratives for analysis and qualitative validation of models. The book presents a systematic application of computational social science methods to the substantive area of extortion racketeering. The reader will gain a deep understanding of extortion rackets, in particular their entrenchment in society and processes supporting and undermining extortion rackets. Also covered are computational social science methods, in particular computationally assisted text analysis and agent-based modelling, and the integration of empirical, theoretical and computational social science.

Edited in collaboration with FoLLI, the Association of Logic, Language and Information, this book constitutes the refereed proceedings of the 23rd International Conference on Formal Grammar, FG 2018, collocated with the European Summer School in Logic, Language and Information in August 2018. The 7 full papers were carefully reviewed and selected from 11 submissions. The focus of papers are as follows: Formal and computational phonology, morphology, syntax, semantics, and pragmatics Model-theoretic and proof-theoretic methods in linguistics Logical aspects of linguistic structure Constraint-based and resource-sensitive approaches to grammar Learnability of formal grammar Integration of stochastic and symbolic models of grammar Foundational, methodological, and architectural issues in grammar and linguistics Mathematical foundations of statistical approaches to linguistic analysis

This book contains the proceedings as well as invited papers for the first annual conference of the UNESCO Unitwin Complex System Digital Campus (CSDC), which is an international initiative gathering 120 Universities on four continents, and structured in ten E-Departments. First Complex Systems Digital Campus World E-Conference 2015 features chapters from the latest research results on theoretical questions of complex systems and their experimental domains. The content contained bridges the gap between the individual and the collective within complex systems science and new integrative sciences on topics such as: genes to organisms to ecosystems, atoms to materials to products, and digital media to the Internet. The conference breaks new ground through a dedicated video-conferencing system - a concept at the heart of the international UNESCO UniTwin, embracing scientists from low-income and distant countries. This book promotes an integrated system of research, education, and training. It also aims at contributing to global development by taking into account its social, economic, and cultural dimensions. First Complex Systems Digital Campus World E-Conference 2015 will appeal to students and researchers working in the fields of complex systems, statistical physics, computational intelligence, and biological physics.

This two-volume set LNCS 10954 and LNCS 10955 constitutes - in conjunction with the volume LNAI 10956 - the refereed proceedings of the 14th International Conference on Intelligent Computing, ICIC 2018, held in Wuhan, China, in August 2018. The 275 full papers and 72 short papers of the three proceedings volumes were carefully reviewed and selected from 632 submissions. The papers are organized in topical sections such as Neural Networks.- Pattern Recognition.- Image Processing.- Intelligent Computing in Robotics.- Intelligent Control and Automation.- Intelligent Data Analysis and Prediction.- Fuzzy Theory and Algorithms.- Supervised Learning.- Unsupervised Learning.- Kernel Methods and Supporting Vector Machines.- Knowledge Discovery and Data Mining.- Natural Language Processing and Computational Linguistics.- Gene Expression Array Analysis.- Systems Biology.- Computational Genomics.- Computational Proteomics.- Gene Regulation Modeling and Analysis.- Protein-Protein Interaction Prediction.- Next-Gen Sequencing and Metagenomics.- Structure Prediction and Folding.- Evolutionary Optimization for Scheduling.- High-Throughput Biomedical Data Integration and Mining.- Machine Learning Algorithms and Applications.- Heuristic Optimization Algorithms for Real-World Applications.- Evolutionary Multi-Objective Optimization and Its Applications.- Swarm Evolutionary Algorithms for Scheduling and Combinatorial.- Optimization.- Swarm Intelligence and Applications in Combinatorial Optimization.- Advances in Metaheuristic Optimization Algorithm.- Advances in Image Processing and Pattern Recognition Techniques.- AI in Biomedicine.- Bioinformatics.- Biometrics Recognition.- Information Security.- Virtual Reality and Human-Computer Interaction.- Healthcare Informatics Theory and Methods.- Intelligent Computing in Computer Vision.- Intelligent Agent and Web Applications.- Reinforcement Learning.- Machine Learning.- Modeling, Simulation, and Optimization of Biological Systems.- Biomedical Data Modeling and Mining.- Cheminformatics.- Intelligent Computing in Computational Biology.- Protein Structure and Function Prediction.- Biomarker Discovery.- Hybrid Computational Intelligence: Theory and Application in Bioinformatics, Computational Biology and Systems Biology.- IoT and Smart Data.- Intelligent Systems and Applications for Bioengineering.- Evolutionary Optimization: Foundations and Its Applications to Intelligent Data Analytics.- Protein and Gene Bioinformatics: Analysis, Algorithms and Applications.

The volume contains original research findings, exchange of ideas and dissemination of innovative, practical development experiences in different fields of soft and advance computing. It provides insights into the International Conference on Soft Computing in Data Analytics (SCDA). It also concentrates on both theory and practices from around the world in all the areas of related disciplines of soft computing. The book provides rapid dissemination of important results in soft computing technologies, a fusion of research in fuzzy logic, evolutionary computations, neural science and neural network systems and chaos theory and chaotic systems, swarm based algorithms, etc. The book aims to cater the postgraduate students and researchers working in the discipline of computer science and engineering along with other engineering branches.

This book constitutes the refereed proceedings of the 13th International Baltic Conference on Databases and Information Systems, DB&IS 2018, held in Trakai, Lithuania, in July 2018. The 24 revised papers presented were carefully reviewed and selected from 69 submissions. The papers are centered around topics like information systems engineering, enterprise information systems, business process management, knowledge representation, ontology engineering, systems security, information systems applications, database systems, machine learning, big data analysis, big data processing, cognitive computing.

This book constitutes the refereed proceedings of the Second International Conference on Emerging Technologies in Computer Engineering: Microservices in Big Data Analytics, ICETCE 2019, held in Jaipur, India, in February 2019. The 28 revised full papers along with 1 short paper presented were carefully reviewed and selected from 253 submissions. ICETCE conference aims to showcase advanced technologies, techniques, innovations and equipments in computer engineering. It provides a platform for researchers, scholars, experts, technicians, government officials and industry personnel from all over the world to discuss and share their valuable ideas and experiences.

This book focuses on the development of wellness protocols for smart home monitoring, aiming to forecast the wellness of individuals living in ambient assisted living (AAL) environments. It describes in detail the design and implementation of heterogeneous wireless sensors and networks as applied to data mining and machine learning, which the protocols are based on. Further, it shows how these sensor and actuator nodes are deployed in the home environment, generating real-time data on object usage and other movements inside the home, and therefore demonstrates that the protocols have proven to offer a reliable, efficient, flexible, and economical solution for smart home systems. Documenting the approach from sensor to decision making and information generation, the book addresses various issues concerning interference mitigation, errors, security and large data handling. As such, it offers a valuable resource for researchers, students and practitioners interested in interdisciplinary studies at the intersection of wireless sensing processing, radio communication, the Internet of Things and machine learning, and in how they can be applied to smart home monitoring and assisted living environments.

This LNAI 1103 constitutes the proceedings of the International Joint Conference on Rough Sets, IJCRS 2018, held in Quy Nhon, Vietnam, in August 2018.The 40 full papers presented together with 5 short papers were carefully reviewed and selected from 61 submissions. The IJCRS conferences aim at bringing together experts from universities and research centers as well as the industry representing fields of research in which theoretical and applicational aspects of rough set theory already find or may potentially find usage.

This two volume set of LNCS 11029 and LNCS 11030 constitutes the refereed proceedings of the 29th International Conference on Database and Expert Systems Applications, DEXA 2018, held in Regensburg, Germany, in September 2018. The 35 revised full papers presented together with 40 short papers were carefully reviewed and selected from 160 submissions. The papers of the first volume discuss a range of topics including: Big data analytics; data integrity and privacy; decision support systems; data semantics; cloud data processing; time series data; social networks; temporal and spatial databases; and graph data and road networks. The papers of the second volume discuss a range of the following topics: Information retrieval; uncertain information; data warehouses and recommender systems; data streams; information networks and algorithms; database system architecture and performance; novel database solutions; graph querying and databases; learning; emerging applications; data mining; privacy; and text processing.

This book offers an overview of knowledge management. It starts with an introduction to the subject, placing descriptive models in the context of the overall field as well as within the more specific field of data mining analysis. Chapter 2 covers data visualization, including directions for accessing R open source software (described through Rattle). Both R and Rattle are free to students. Chapter 3 then describes market basket analysis, comparing it with more advanced models, and addresses the concept of lift. Subsequently, Chapter 4 describes smarketing RFM models and compares it with more advanced predictive models. Next, Chapter 5 describes association rules, including the APriori algorithm and provides software support from R. Chapter 6 covers cluster analysis, including software support from R (Rattle), KNIME, and WEKA, all of which are open source. Chapter 7 goes on to describe link analysis, social network metrics, and open source NodeXL software, and demonstrates link analysis application using PolyAnalyst output. Chapter 8 concludes the monograph. Using business-related data to demonstrate models, this descriptive book explains how methods work with some citations, but without detailed references. The data sets and software selected are widely available and can easily be accessed.

This book presents practical approaches for facilitating the achievement of excellence in the management and leadership of organizational resources. It shows how the principles of creating shared value can be applied to ensure faster learning, training, business development, and social renewal. In particular, it presents novel methods and tools for tackling the complexity of management and learning in both business organizations and society. Discussing ontologies, intelligent management systems, methods for creating knowledge and value added, it offers novel insights into time management and operations optimization, as well as advanced methods for evaluating customers' satisfaction and conscious experience. Based on two conferences, the AHFE 2018 International Conference on Human Factors, Business Management and Society, and the AHFE 2018 International Conference on Human Factors in Management and Leadership, held on July 21-25, 2018, in Orlando, Florida, USA, the book provides both researchers and professionals with new tools and inspiring ideas for achieving excellence in various business activities. Chapter "Convolutional Gravitational Models for Economic Exchanges: Mathematical Extensions for Dynamic Processes and Knowledge Flows" is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.

This book offers researchers an understanding of the fundamental issues and a good starting point to work on this rapidly expanding field. It provides a comprehensive survey of current developments of heterogeneous information network. It also presents the newest research in applications of heterogeneous information networks to similarity search, ranking, clustering, recommendation. This information will help researchers to understand how to analyze networked data with heterogeneous information networks. Common data mining tasks are explored, including similarity search, ranking, and recommendation. The book illustrates some prototypes which analyze networked data. Professionals and academics working in data analytics, networks, machine learning, and data mining will find this content valuable. It is also suitable for advanced-level students in computer science who are interested in networking or pattern recognition.

This book focuses on new and emerging data mining solutions that offer a greater level of transparency than existing solutions. Transparent data mining solutions with desirable properties (e.g. effective, fully automatic, scalable) are covered in the book. Experimental findings of transparent solutions are tailored to different domain experts, and experimental metrics for evaluating algorithmic transparency are presented. The book also discusses societal effects of black box vs. transparent approaches to data mining, as well as real-world use cases for these approaches.As algorithms increasingly support different aspects of modern life, a greater level of transparency is sorely needed, not least because discrimination and biases have to be avoided. With contributions from domain experts, this book provides an overview of an emerging area of data mining that has profound societal consequences, and provides the technical background to for readers to contribute to the field or to put existing approaches to practical use.

This book reports on the latest advances on the theories, practices, standards and strategies that are related to the modern technology paradigms, the Mobile Cloud computing (MCC) and Big Data, as the pillars and their association with the emerging 5G mobile networks. The book includes 15 rigorously refereed chapters written by leading international researchers, providing the readers with technical and scientific information about various aspects of Big Data and Mobile Cloud Computing, from basic concepts to advanced findings, reporting the state-of-the-art on Big Data management. It demonstrates and discusses methods and practices to improve multi-source Big Data manipulation techniques, as well as the integration of resources availability through the 3As (Anywhere, Anything, Anytime) paradigm, using the 5G access technologies.