Jon Rokne – författare

The Encyclopedia of Social Network Analysis and Mining (ESNAM) is the first major reference work to integrate fundamental concepts and research directions in the areas of social networks and applications to data mining.

This book details how electronic health records (EHRs) and medical records (EMRs) can be optimized to enable meaningful interactions between provider and patient to enhance quality of care in this new era of mHealth. As the technologies evolve to provide greater opportunities for mHealth applications, so do the challenges. This book addresses the issues of interoperability limitations, data processing errors and patient data privacy while providing instruction on how blockchain-like processes can potentially ensure the integrity of an externally maintained EHR.Portable Health Records in a Mobile Society identifies important issues and promising solutions to create a truly portable EHRs. It is a valuable resource for all informaticians and healthcare providers seeking an up-to-date resource on how to improve the availability, reliability, integrity and sustainability of these revolutionary developments in healthcare management.

This book details how electronic health records (EHRs) and medical records (EMRs) can be optimized to enable meaningful interactions between provider and patient to enhance quality of care in this new era of mHealth.

This book presents the state-of-the-art in various aspects of analysis and mining of online social networks. Within the broader context of online social networks, it focuses on important and upcoming topics of social network analysis and mining such as the latest in sentiment trends research and a variety of techniques for community detection and analysis. The book collects chapters that are expanded versions of the best papers presented at the IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM’2015), which was held in Paris, France in August 2015. All papers have been peer reviewed and checked carefully for overlap with the literature. The book will appeal to students and researchers in social network analysis/mining and machine learning.

This book presents the state-of-the-art in various aspects of analysis and mining of online social networks.

The study of social networks was originated in social and business communities. In recent years, social network research has advanced significantly; the development of sophisticated techniques for Social Network Analysis and Mining (SNAM) has been highly influenced by the online social Web sites, email logs, phone logs and instant messaging systems, which are widely analyzed using graph theory and machine learning techniques. People perceive the Web increasingly as a social medium that fosters interaction among people, sharing of experiences and knowledge, group activities, community formation and evolution. This has led to a rising prominence of SNAM in academia, politics, homeland security and business. This follows the pattern of known entities of our society that have evolved into networks in which actors are increasingly dependent on their structural embedding General areas of interest to the book include information science and mathematics, communication studies, business and organizational studies, sociology, psychology, anthropology, applied linguistics, biology and medicine.

The study of social networks was originated in social and business communities. In recent years, social network research has advanced significantly; the development of sophisticated techniques for Social Network Analysis and Mining (SNAM) has been highly influenced by the online social Web sites, email logs, phone logs and instant messaging systems, which are widely analyzed using graph theory and machine learning techniques. People perceive the Web increasingly as a social medium that fosters interaction among people, sharing of experiences and knowledge, group activities, community formation and evolution. This has led to a rising prominence of SNAM in academia, politics, homeland security and business. This follows the pattern of known entities of our society that have evolved into networks in which actors are increasingly dependent on their structural embedding General areas of interest to the book include information science and mathematics, communication studies, business and organizational studies, sociology, psychology, anthropology, applied linguistics, biology and medicine.

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 fastgrowing field of cybersecurity.