Social Network Based Recommender Systems

This book introduces novel techniques and algorithms necessary to support the formation of social networks. Concepts such as link prediction, graph patterns, recommendation systems based on user reputation, strategic partner selection, collaborative systems and network formation based on ‘social brokers’ are presented. Chapters cover a wide range of models and algorithms, including graph models and a personalized PageRank model. Extensive experiments and scenarios using real world datasets from GitHub, Facebook, Twitter, Google Plus and the European Union ICT research collaborations serve to enhance reader understanding of the material with clear applications. Each chapter concludes with an analysis and detailed summary. Social Network-Based Recommender Systems is designed as a reference for professionals and researchers working in social network analysis and companies working on recommender systems. Advanced-level students studying computer science, statistics or mathematics will also find this books useful as a secondary text.

Online social networks collect information from users' social contacts and their daily interactions (co-tagging of photos, co-rating of products etc.) to provide them with recommendations of new products or friends. Lately, technological progressions in mobile devices (i.e. smart phones) enabled the incorporation of geo-location data in the traditional web-based online social networks, bringing the new era of Social and Mobile Web. The goal of this book is to bring together important research in a new family of recommender systems aimed at serving Location-based Social Networks (LBSNs). The chapters introduce a wide variety of recent approaches, from the most basic to the state-of-the-art, for providing recommendations in LBSNs. The book is organized into three parts. Part 1 provides introductory material on recommender systems, online social networks and LBSNs. Part 2 presents a wide variety of recommendation algorithms, ranging from basic to cutting edge, as well as a comparison of the characteristics of these recommender systems. Part 3 provides a step-by-step case study on the technical aspects of deploying and evaluating a real-world LBSN, which provides location, activity and friend recommendations. The material covered in the book is intended for graduate students, teachers, researchers, and practitioners in the areas of web data mining, information retrieval, and machine learning.

This book contains papers presented at the 5th Atlantic Web Intelligence Conference, AWIC’2007, held in Fontainbleau, France, in June 2007, and organized by Esigetel, Technical University of Lodz, and Polish Academy of Sciences. It includes reports from the front of diverse fields of the Web, including application of artificial intelligence, design, information retrieval and interpretation, user profiling, security, and engineering.

Driven by counter-terrorism efforts, marketing analysis and an explosion in online social networking in recent years, data mining has moved to the forefront of information science. This proposed Special Issue on Data Mining for Social Network Data will present a broad range of recent studies in social networking analysis. It will focus on emerging trends and needs in discovery and analysis of communities, solitary and social activities, activities in open for a and commercial sites as well. It will also look at network modeling, infrastructure construction, dynamic growth and evolution pattern discovery using machine learning approaches and multi-agent based simulations. Editors are three rising stars in world of data mining, knowledge discovery, social network analysis, and information infrastructures, and are anchored by Springer author/editor Hsinchun Chen (Terrorism Informatics; Medical Informatics; Digital Government), who is one of the most prominent intelligence analysis and data mining experts in the world.

The recommendation of products, content and services cannot be considered newly born, although its widespread application is still in full swing. While its growing success in numerous sectors, the progress of the Social Web has revolutionized the architecture of participation and relationship in the Web, making it necessary to restate recommendation and reconciling it with Collaborative Tagging, as the popularization of authoring in the Web, and Social Networking, as the translation of personal relationships to the Web. Precisely, the convergence of recommendation with the above Social Web pillars is what motivates this book, which has collected contributions from well-known experts in the academy and the industry to provide a broader view of the problems that Social Recommenders might face with. If recommender systems have proven their key role in facilitating the user access to resources on the Web, when sharing resources has become social, it is natural for recommendation strategies in the Social Web era take into account the users’ point of view and the relationships among users to calculate their predictions. This book aims to help readers to discover and understand the interplay among legal issues such as privacy; technical aspects such as interoperability and scalability; and social aspects such as the influence of affinity, trust, reputation and likeness, when the goal is to offer recommendations that are truly useful to both the user and the provider.

This edited volume offers a clear in-depth overview of research covering a variety of issues in social search and recommendation systems. Within the broader context of social network analysis it focuses on important and up-coming topics such as real-time event data collection, frequent-sharing pattern mining, improvement of computer-mediated communication, social tagging information, search system personalization, new detection mechanisms for the identification of online user groups, and many more. The twelve contributed chapters are extended versions of conference papers as well as completely new invited chapters in the field of social search and recommendation systems. This first-of-its kind survey of current methods will be of interest to researchers from both academia and industry working in the field of social networks.

The International Symposium on Distributed Computing and Artificial Intelligence is an annual forum that brings together ideas, projects, lessons, etc. associated with distr- uted computing, artificial intelligence and its applications in different themes. This meeting has been held at the University of Salamanca from the 22th to the 24th of October 2008. This symposium has be organized by the Biomedicine, Intelligent S- tem and Educational Technology Research Group (http://bisite. usal. es/) of the Univ- sity of Salamanca. The technology transfer in this field is still a challenge and for that reason this type of contributions has been specially considered in this edition. This c- ference is the forum in which to present application of innovative techniques to complex problems. The artificial intelligence is changing our society. Its application in distr- uted environments, such as the Internet, electronic commerce, mobile communications, wireless devices, distributed computing, and so on is increasing and is becoming an element of high added value and economic potential, both industrial and research. These technologies are changing constantly as a result of the large research and technical effort being undertaken in both universities and businesses. The exchange of ideas between scientists and technicians from both academic and business areas is essential to facilitate the development of systems that meet the demands of today's society.

The main target of this book is to raise the awareness about social networking systems design, implementation, security requirements, and approaches. The book entails related issues including computing, engineering, security, management, and organization policy. It interprets the design, implementation and security threats in the social networks and offers some solutions in this concern. It clarifies the authentication concept between servers to identity users. Most of the models that focus on protecting users’ information are also included. This book introduces the Human-Interactive Security Protocols (HISPs) efficiently. Presenting different types of the social networking systems including the internet and mobile devices is one of the main targets of this book. This book includes the social network performance evaluation metrics. It compares various models and approaches used in the design of the social networks. This book includes various applications for the use of the social networks in the healthcare, e-commerce, crisis management, and academic applications. The book provides an extensive background for the development of social network science and its challenges. This book discusses the social networks integration to offer online services, such as instant messaging, email, file sharing, transferring patients’ medical reports/images, location-based recommendations and many other functions. This book provides users, designers, engineers and managers with the valuable knowledge to build a better secured information transfer over the social networks. The book gathers remarkable materials from an international experts’ panel to guide the readers during the analysis, design, implementation and security achievement for the social network systems. In this book, theories, practical guidance, and challenges are included to inspire designers and researchers. The book guides the engineers, designers, and researchers to exploit the intrinsic design of the social network systems.