This book explains aspects of social networks, varying from development and application of new artificial intelligence and computational intelligence techniques for social networks to understanding the impact of social networks. Chapters 1 and 2 deal with the basic strategies towards social networks such as mining text from such networks and applying social network metrics using a hybrid approach; Chaps. 3 to 8 focus on the prime research areas in social networks: community detection, influence maximization and opinion mining. Chapter 9 to 13 concentrate on studying the impact and use of social networks in society, primarily in education, commerce, and crowd sourcing. The contributions provide a multidimensional approach, and the book will serve graduate students and researchers as a reference in computer science, electronics engineering, communications, and information technology.

Hybrid Computational Intelligent Systems – Modeling, Simulation and Optimization unearths the latest advances in evolving hybrid intelligent modeling and simulation of human-centric data-intensive applications optimized for real-time use, thereby enabling researchers to come up with novel breakthroughs in this ever-growing field. Salient features include the fundamentals of modeling and simulation with recourse to knowledge-based simulation, interaction paradigms, and human factors, along with the enhancement of the existing state of art in a high-performance computing setup. In addition, this book presents optimization strategies to evolve robust and failsafe intelligent system modeling and simulation. The volume also highlights novel applications for different engineering problems including signal and data processing, speech, image, sensor data processing, innovative intelligent systems, and swarm intelligent manufacturing systems. Features: A self-contained approach to integrating the principles of hybrid computational ntelligence with system modeling and simulation Well-versed foundation of computational intelligence and its application to real life engineering problems Elucidates essential background, concepts, definitions, and theories thereby putting forward a complete treatment on the subject Effective modeling of hybrid intelligent systems forms the backbone of almost every operative system in real-life Proper simulation of real-time hybrid intelligent systems is a prerequisite for deriving any real-life system solution Optimized system modeling and simulation enable real-time and failsafe operations of the existing hybrid intelligent system solutions Information presented in an accessible way for researchers, engineers, developers, and practitioners from academia and industry working in all major areas and interdisciplinary areas of hybrid computational intelligence and communication systems to evolve human-centered modeling and simulations of real-time data-intensive intelligent systems.

This book highlights recent research on Hybrid Intelligent Systems and their various practical applications. It presents 56 selected papers from the 18th International Conference on Hybrid Intelligent Systems (HIS 2018), which was held at the Instituto Superior de Engenharia do Porto (ISEP), Porto, Portugal from December 13 to 15, 2018. A premier conference in the field of Artificial Intelligence, HIS 2018 brought together researchers, engineers and practitioners whose work involves intelligent systems and their applications in industry. Including contributions by authors from over 30 countries, the book offers a valuable reference guide for all researchers, students and practitioners in the fields of Computer Science and Engineering.

This book highlights the recent research on hybrid intelligent systems and their various practical applications. It presents 58 selected papers from the 20th International Conference on Hybrid Intelligent Systems (HIS 2020) and 20 papers from the 12th World Congress on Nature and Biologically Inspired Computing (NaBIC 2020), which was held online, from December 14 to 16, 2020. A premier conference in the field of artificial intelligence, HIS - NaBIC 2020 brought together researchers, engineers and practitioners whose work involves intelligent systems, network security and their applications in industry. Including contributions by authors from 25 countries, the book offers a valuable reference guide for all researchers, students and practitioners in the fields of science and engineering.

Conventional computational methods, and even the latest soft computing paradigms, often fall short in their ability to offer solutions to many real-world problems due to uncertainty, imprecision, and circumstantial data. Hybrid intelligent computing is a paradigm that addresses these issues to a considerable extent. The Handbook of Research on Advanced Hybrid Intelligent Techniques and Applications highlights the latest research on various issues relating to the hybridization of artificial intelligence, practical applications, and best methods for implementation. Focusing on key interdisciplinary computational intelligence research dealing with soft computing techniques, pattern mining, data analysis, and computer vision, this book is relevant to the research needs of academics, IT specialists, and graduate-level students.

This book gathers selected research papers presented at the International Conference on Communication and Intelligent Systems (ICCIS 2020), organized jointly by Birla Institute of Applied Sciences, Uttarakhand, and Soft Computing Research Society during 26–27 December 2020. This book presents a collection of state-of-the-art research work involving cutting-edge technologies for communication and intelligent systems. Over the past few years, advances in artificial intelligence and machine learning have sparked new research efforts around the globe, which explore novel ways of developing intelligent systems and smart communication technologies. The book presents single- and multi-disciplinary research on these themes in order to make the latest results available in a single, readily accessible source.

The two LNAI volumes 7208 and 7209 constitute the proceedings of the 7th International Conference on Hybrid Artificial Intelligent Systems, HAIS 2012, held in Salamanca, Spain, in March 2012. The 118 papers published in these proceedings were carefully reviewed and selected from 293 submissions. They are organized in topical sessions on agents and multi agents systems, HAIS applications, cluster analysis, data mining and knowledge discovery, evolutionary computation, learning algorithms, systems, man, and cybernetics by HAIS workshop, methods of classifier fusion, HAIS for computer security (HAISFCS), data mining: data preparation and analysis, hybrid artificial intelligence systems in management of production systems, hybrid artificial intelligent systems for ordinal regression, hybrid metaheuristics for combinatorial optimization and modelling complex systems, hybrid computational intelligence and lattice computing for image and signal processing and nonstationary models of pattern recognition and classifier combinations.

Computational collective intelligence (CCI) is most often understood as a subfield of artificial intelligence (AI) dealing with soft computing methods that enable group decisions to be made or knowledge to be processed among autonomous units acting in distributed environments. The needs for CCI techniques and tools have grown signi- cantly recently as many information systems work in distributed environments and use distributed resources. Web-based systems, social networks and multi-agent systems very often need these tools for working out consistent knowledge states, resolving conflicts and making decisions. Therefore, CCI is of great importance for today’s and future distributed systems. Methodological, theoretical and practical aspects of computational collective int- ligence, such as group decision making, collective action coordination, and knowledge integration, are considered as the form of intelligence that emerges from the collabo- tion and competition of many individuals (artificial and/or natural). The application of multiple computational intelligence technologies such as fuzzy systems, evolutionary computation, neural systems, consensus theory, etc. , can support human and other collective intelligence and create new forms of CCI in natural and/or artificial s- tems.

Given the widespread, frequent use of social networks as a means for people to communicate and share their interests, it comes as no surprise that they have become an important tool for businesses and business networking. The Handbook of Research on Business Social Networking: Organizational, Managerial, and Technological Dimensions investigates the beginning of social networks and provides perspectives on how they can enhance business. This two-volume reference discusses the main issues, challenges, opportunities, and trends related to the range of new developments and applications in business social networking. Social networks and their integration in businesses are be addressed using technological, organizational, managerial, and social perspectives with the aim of disseminating current developments, case studies, new integrated approaches, and practical solutions and applications.

Previous studies revealed that around 75 percent of all start-ups fail at an early stage. One main reason for this tremendous failure rate is that entrepreneurs are typically confronted with high levels of uncertainty about the viability of their proposed business idea. Following this argumentation, entrepreneurial decision-making can be defined as complex decision-making problem under both risk and uncertainty. While risk includes quantifiable probabilities, uncertainty describes situations where neither outcomes nor their probability distribution can be assessed a priori. Consequently, the entrepreneurial decision-making context is highly complex and contains lots of “black swan events” that seems to be unpredictable. As previous research does not provide any IT-based and scalable solutions for decisional guidance in such contexts, the purpose of this study is to explore the entrepreneurial decision- making context and then suggest novel and innovative design paradigms and design principles for decisional guidance in the context of entrepreneurial decision-making.