Social Network Algorithms

This book focuses on the following three key topics in social network large-scale decision-making: structure-heterogeneous information fusion, clustering analysis with multiple measurement attributes, and consensus building considering trust loss. To address the aggregation and distance measurement of structure-heterogeneous evaluation information, we propose a fusion method based on trust and behavior analysis. Then, two clustering algorithms are put forward, including trust Cop-K-means clustering algorithm and compatibility distance-oriented off-center clustering algorithm. The above clustering algorithms emphasize the similarity of opinions and social relationships as important measurement attributes of clustering. Finally, this book explores the impact of trust loss originating from social relationships on the CRP and develops two consensus-reaching models, namely the improved minimum-cost consensus model that takes into account voluntary trust loss and the punishment-driven consensus-reaching model. Some case studies, a large number of numerical experiments, and comparative analyses are provided in this book to demonstrate the characteristics and advantages of the proposed methods and models.

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.

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.

This book presents the proceedings of the International Conference on Emerging Research in Computing, Information, Communication and Applications (ERCICA) 2023. The conference provides an interdisciplinary forum for researchers, professional engineers and scientists, educators and technologists to discuss, debate and promote research and technology in the upcoming areas of computing, information, communication and their applications. Some of the topics include the Internet of Things (IoT), wireless communications, image and video processing, parallel and distributed computing, and smart grid applications, among others. The book discusses these emerging research areas, providing a valuable resource for researchers and practicing engineers alike.

This book presents practical development experiences in different areas of data analysis and pattern recognition, focusing on soft computing technologies, clustering and classification algorithms, rough set and fuzzy set theory, evolutionary computations, neural science and neural network systems, image processing, combinatorial pattern matching, social network analysis, audio and video data analysis, data mining in dynamic environments, bioinformatics, hybrid computing, big data analytics and deep learning. It also provides innovative solutions to the challenges in these areas and discusses recent developments.

This book presents practical development experiences in different areas of data analysis and pattern recognition, focusing on soft computing technologies, clustering and classification algorithms, rough set and fuzzy set theory, evolutionary computations, neural science and neural network systems, image processing, combinatorial pattern matching, social network analysis, audio and video data analysis, data mining in dynamic environments, bioinformatics, hybrid computing, big data analytics and deep learning. It also provides innovative solutions to the challenges in these areas and discusses recent developments.