Social Networking And Computational Intelligence
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| Author | : Rajesh Kumar Shukla |
| Publisher | : Springer Nature |
| Total Pages | : 789 |
| Release | : 2020-03-21 |
| Genre | : Technology & Engineering |
| ISBN | : 9811520712 |
This book presents a selection of revised and extended versions of the best papers from the First International Conference on Social Networking and Computational Intelligence (SCI-2018), held in Bhopal, India, from October 5 to 6, 2018. It discusses recent advances in scientific developments and applications in these areas.
| Author | : Wendy W. Moe |
| Publisher | : Cambridge University Press |
| Total Pages | : 205 |
| Release | : 2014-02-24 |
| Genre | : Computers |
| ISBN | : 1107656036 |
In the world of Facebook, Twitter and Yelp, water-cooler conversations with co-workers and backyard small talk with neighbors have moved from the physical world to the digital arena. In this new landscape, organizations ranging from Fortune 500 companies to government agencies to political campaigns continuously monitor online opinions in an effort to guide their actions. Are consumers satisfied with our product? How are our policies perceived? Do voters agree with our platform? Measuring online opinion is more complex than just reading a few posted reviews. Social media is replete with noise and chatter that can contaminate monitoring efforts. By knowing what shapes online opinions, organizations can better uncover the valuable insights hidden in the social media chatter and better inform strategy. This book can help anyone facing the challenge of making sense of social media data to move beyond the current practice of social media monitoring to a more comprehensive use of social media intelligence.
| Author | : Manasvi Aggarwal |
| Publisher | : Springer Nature |
| Total Pages | : 121 |
| Release | : 2020-11-25 |
| Genre | : Technology & Engineering |
| ISBN | : 9813340223 |
This book deals with network representation learning. It deals with embedding nodes, edges, subgraphs and graphs. There is a growing interest in understanding complex systems in different domains including health, education, agriculture and transportation. Such complex systems are analyzed by modeling, using networks that are aptly called complex networks. Networks are becoming ubiquitous as they can represent many real-world relational data, for instance, information networks, molecular structures, telecommunication networks and protein–protein interaction networks. Analysis of these networks provides advantages in many fields such as recommendation (recommending friends in a social network), biological field (deducing connections between proteins for treating new diseases) and community detection (grouping users of a social network according to their interests) by leveraging the latent information of networks. An active and important area of current interest is to come out with algorithms that learn features by embedding nodes or (sub)graphs into a vector space. These tasks come under the broad umbrella of representation learning. A representation learning model learns a mapping function that transforms the graphs' structure information to a low-/high-dimension vector space maintaining all the relevant properties.
| Author | : Yulei Wu |
| Publisher | : CRC Press |
| Total Pages | : 530 |
| Release | : 2017-12-14 |
| Genre | : Computers |
| ISBN | : 1498784879 |
This book presents state-of-the-art solutions to the theoretical and practical challenges stemming from the leverage of big data and its computational intelligence in supporting smart network operation, management, and optimization. In particular, the technical focus covers the comprehensive understanding of network big data, efficient collection and management of network big data, distributed and scalable online analytics for network big data, and emerging applications of network big data for computational intelligence.
| Author | : Witold Pedrycz |
| Publisher | : Springer |
| Total Pages | : 440 |
| Release | : 2013-12-09 |
| Genre | : Technology & Engineering |
| ISBN | : 3319029932 |
This volume provides the audience with an updated, in-depth and highly coherent material on the conceptually appealing and practically sound information technology of Computational Intelligence applied to the analysis, synthesis and evaluation of social networks. The volume involves studies devoted to key issues of social networks including community structure detection in networks, online social networks, knowledge growth and evaluation, and diversity of collaboration mechanisms. The book engages a wealth of methods of Computational Intelligence along with well-known techniques of linear programming, Formal Concept Analysis, machine learning, and agent modeling. Human-centricity is of paramount relevance and this facet manifests in many ways including personalized semantics, trust metric, and personal knowledge management; just to highlight a few of these aspects. The contributors to this volume report on various essential applications including cyber attacks detection, building enterprise social networks, business intelligence and forming collaboration schemes. Given the subject area, this book is aimed at a broad audience of researchers and practitioners. Owing to the nature of the material being covered and a way it is organized, the volume will appeal to the well-established communities including those active in various disciplines in which social networks, their analysis and optimization are of genuine relevance. Those involved in operations research, management, various branches of engineering, and economics will benefit from the exposure to the subject matter.
| Author | : Mohamed Lahby |
| Publisher | : Springer Nature |
| Total Pages | : 432 |
| Release | : 2021-12-15 |
| Genre | : Technology & Engineering |
| ISBN | : 3030900878 |
This book presents the latest cutting-edge research, theoretical methods, and novel applications in the field of computational intelligence techniques and methods for combating fake news. Fake news is everywhere. Despite the efforts of major social network players such as Facebook and Twitter to fight disinformation, miracle cures and conspiracy theories continue to rain down on the net. Artificial intelligence can be a bulwark against the diversity of fake news on the Internet and social networks. This book discusses new models, practical solutions, and technological advances related to detecting and analyzing fake news based on computational intelligence models and techniques, to help decision-makers, managers, professionals, and researchers design new paradigms considering the unique opportunities associated with computational intelligence techniques. Further, the book helps readers understand computational intelligence techniques combating fake news in a systematic and straightforward way.
| Author | : Janmenjoy Nayak |
| Publisher | : Springer Nature |
| Total Pages | : 569 |
| Release | : 2021-07-27 |
| Genre | : Technology & Engineering |
| ISBN | : 3030747611 |
This book provides a comprehensive description of the novel coronavirus infection, spread analysis, and related challenges for the effective combat and treatment. With a detailed discussion on the nature of transmission of COVID-19, few other important aspects such as disease symptoms, clinical application of radiomics, image analysis, antibody treatments, risk analysis, drug discovery, emotion and sentiment analysis, virus infection, and fatality prediction are highlighted. The main focus is laid on different issues and futuristic challenges of computational intelligence techniques in solving and identifying the solutions for COVID-19. The book drops radiance on the reasons for the growing profusion and complexity of data in this sector. Further, the book helps to focus on further research challenges and directions of COVID-19 for the practitioners as well as researchers.
| Author | : Andries P. Engelbrecht |
| Publisher | : John Wiley & Sons |
| Total Pages | : 628 |
| Release | : 2007-10-22 |
| Genre | : Technology & Engineering |
| ISBN | : 9780470512500 |
Computational Intelligence: An Introduction, Second Edition offers an in-depth exploration into the adaptive mechanisms that enable intelligent behaviour in complex and changing environments. The main focus of this text is centred on the computational modelling of biological and natural intelligent systems, encompassing swarm intelligence, fuzzy systems, artificial neutral networks, artificial immune systems and evolutionary computation. Engelbrecht provides readers with a wide knowledge of Computational Intelligence (CI) paradigms and algorithms; inviting readers to implement and problem solve real-world, complex problems within the CI development framework. This implementation framework will enable readers to tackle new problems without any difficulty through a single Java class as part of the CI library. Key features of this second edition include: A tutorial, hands-on based presentation of the material. State-of-the-art coverage of the most recent developments in computational intelligence with more elaborate discussions on intelligence and artificial intelligence (AI). New discussion of Darwinian evolution versus Lamarckian evolution, also including swarm robotics, hybrid systems and artificial immune systems. A section on how to perform empirical studies; topics including statistical analysis of stochastic algorithms, and an open source library of CI algorithms. Tables, illustrations, graphs, examples, assignments, Java code implementing the algorithms, and a complete CI implementation and experimental framework. Computational Intelligence: An Introduction, Second Edition is essential reading for third and fourth year undergraduate and postgraduate students studying CI. The first edition has been prescribed by a number of overseas universities and is thus a valuable teaching tool. In addition, it will also be a useful resource for researchers in Computational Intelligence and Artificial Intelligence, as well as engineers, statisticians, operational researchers, and bioinformaticians with an interest in applying AI or CI to solve problems in their domains. Check out http://www.ci.cs.up.ac.za for examples, assignments and Java code implementing the algorithms.
| Author | : Leonard Barolli |
| Publisher | : Springer |
| Total Pages | : 1217 |
| Release | : 2019-03-14 |
| Genre | : Technology & Engineering |
| ISBN | : 3030150356 |
The aim of the book is to provide latest research findings, innovative research results, methods and development techniques from both theoretical and practical perspectives related to the emerging areas of Web Computing, Intelligent Systems and Internet Computing. As the Web has become a major source of information, techniques and methodologies that extract quality information are of paramount importance for many Web and Internet applications. Data mining and knowledge discovery play key roles in many of today’s prominent Web applications such as e-commerce and computer security. Moreover, the outcome of Web services delivers a new platform for enabling service-oriented systems. The emergence of large scale distributed computing paradigms, such as Cloud Computing and Mobile Computing Systems, has opened many opportunities for collaboration services, which are at the core of any Information System. Artificial Intelligence (AI) is an area of computer science that build intelligent systems and algorithms that work and react like humans. The AI techniques and computational intelligence are powerful tools for learning, adaptation, reasoning and planning. They have the potential to become enabling technologies for the future intelligent networks. Recent research in the field of intelligent systems, robotics, neuroscience, artificial intelligence and cognitive sciences are very important for the future development and innovation of Web and Internet applications.
| Author | : Abassi, Ryma |
| Publisher | : IGI Global |
| Total Pages | : 309 |
| Release | : 2019-01-25 |
| Genre | : Computers |
| ISBN | : 1522573542 |
The recent rise of emerging networking technologies such as social networks, content centric networks, Internet of Things networks, etc, have attracted significant attention from academia as well as industry professionals looking to utilize these technologies for efficiency purposes. However, the allure of such networks and resultant storage of high volumes of data leads to increased security risks, including threats to information privacy. Artificial Intelligence and Security Challenges in Emerging Networks is an essential reference source that discusses applications of artificial intelligence, machine learning, and data mining, as well as other tools and strategies to protect networks against security threats and solve security and privacy problems. Featuring research on topics such as encryption, neural networks, and system verification, this book is ideally designed for ITC procurement managers, IT consultants, systems and network integrators, infrastructure service providers, computer and software engineers, startup companies, academicians, researchers, managers, and students.
