Social Network Based Recommender Systems

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Social Network-Based Recommender Systems

Author : Daniel Schall
Publisher : Springer
Page : 126 pages
File Size : 43,7 Mb
Release : 2015-09-23
Category : Computers
ISBN : 9783319227351

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Social Network-Based Recommender Systems by Daniel Schall Pdf

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.

Recommender Systems for Location-based Social Networks

Author : Panagiotis Symeonidis,Dimitrios Ntempos,Yannis Manolopoulos
Publisher : Springer Science & Business Media
Page : 109 pages
File Size : 50,9 Mb
Release : 2014-02-08
Category : Computers
ISBN : 9781493902866

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Recommender Systems for Location-based Social Networks by Panagiotis Symeonidis,Dimitrios Ntempos,Yannis Manolopoulos Pdf

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.

Data Mining for Social Network Data

Author : Nasrullah Memon,Jennifer Jie Xu,David L. Hicks,Hsinchun Chen
Publisher : Springer Science & Business Media
Page : 217 pages
File Size : 50,6 Mb
Release : 2010-06-10
Category : Business & Economics
ISBN : 9781441962874

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Data Mining for Social Network Data by Nasrullah Memon,Jennifer Jie Xu,David L. Hicks,Hsinchun Chen Pdf

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.

Advances in Intelligent Web Mastering

Author : Katarzyna M. Wegrzyn-Wolska,Piotr S. Szczepaniak
Publisher : Springer Science & Business Media
Page : 413 pages
File Size : 54,5 Mb
Release : 2007-06-15
Category : Computers
ISBN : 9783540725749

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Advances in Intelligent Web Mastering by Katarzyna M. Wegrzyn-Wolska,Piotr S. Szczepaniak Pdf

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.

Cooperative Information Agents VIII

Author : Matthias Klusch,Sascha Ossowski,Vipul Kashyap,Rainer Unland
Publisher : Springer Science & Business Media
Page : 314 pages
File Size : 42,7 Mb
Release : 2004-09-23
Category : Computers
ISBN : 9783540231707

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Cooperative Information Agents VIII by Matthias Klusch,Sascha Ossowski,Vipul Kashyap,Rainer Unland Pdf

These are the proceedings of the 8th International Workshop on Cooperative Information Agents (CIA 2004), held at the Fair and Congress Center in - furt, Germany, September 27–29, 2004. It was part of the multi-conference Net. ObjectDays 2004, and, in particular, was co-located with the 2nd German Conference on Multiagent Systems Technologies (MATES 2004). In today’s networked world of linked heterogeneous, pervasive computer systems, devices, and information landscapes, the intelligent coordination and provision of relevant added-value information at any time, anywhere, by means of cooperative information agents becomes increasingly important for a variety of applications. An information agent is a computational software entity that has access to one or multiple, heterogeneous, and geographically dispersed data and information sources. It proactively searches for and maintains information on behalf of its human users, or other agents, preferably just in time. In other words,itismanagingandovercomingthedi?cultiesassociatedwithinformation overload in open, pervasive information and service landscapes. Cooperative - formation agents may collaborate with each other to accomplish both individual and shared joint goals depending on the actual preferences of their users, b- getary constraints, and resources available. One major challenge of developing agent-based intelligent information systems in open environments is to balance the autonomy of networked data, information, and knowledge sources with the potential payo? of leveraging them using information agents. Interdisciplinaryresearchanddevelopmentofinformationagentsrequires- pertise in relevant domains of information retrieval, arti?cial intelligence, database systems, human-computer interaction, and Internet and Web techn- ogy.

Recommender Systems

Author : Charu C. Aggarwal
Publisher : Springer
Page : 498 pages
File Size : 54,5 Mb
Release : 2016-03-28
Category : Computers
ISBN : 9783319296593

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Recommender Systems by Charu C. Aggarwal Pdf

This book comprehensively covers the topic of recommender systems, which provide personalized recommendations of products or services to users based on their previous searches or purchases. Recommender system methods have been adapted to diverse applications including query log mining, social networking, news recommendations, and computational advertising. This book synthesizes both fundamental and advanced topics of a research area that has now reached maturity. The chapters of this book are organized into three categories: Algorithms and evaluation: These chapters discuss the fundamental algorithms in recommender systems, including collaborative filtering methods, content-based methods, knowledge-based methods, ensemble-based methods, and evaluation. Recommendations in specific domains and contexts: the context of a recommendation can be viewed as important side information that affects the recommendation goals. Different types of context such as temporal data, spatial data, social data, tagging data, and trustworthiness are explored. Advanced topics and applications: Various robustness aspects of recommender systems, such as shilling systems, attack models, and their defenses are discussed. In addition, recent topics, such as learning to rank, multi-armed bandits, group systems, multi-criteria systems, and active learning systems, are introduced together with applications. Although this book primarily serves as a textbook, it will also appeal to industrial practitioners and researchers due to its focus on applications and references. Numerous examples and exercises have been provided, and a solution manual is available for instructors.

Recommender Systems for the Social Web

Author : José J. Pazos Arias,Ana Fernández Vilas,Rebeca P. Díaz Redondo
Publisher : Springer Science & Business Media
Page : 226 pages
File Size : 53,7 Mb
Release : 2012-01-24
Category : Technology & Engineering
ISBN : 9783642256943

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Recommender Systems for the Social Web by José J. Pazos Arias,Ana Fernández Vilas,Rebeca P. Díaz Redondo Pdf

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.

Recommender Systems: Advanced Developments

Author : Jie Lu,Qian Zhang,Guang-quan Zhang
Publisher : World Scientific
Page : 362 pages
File Size : 40,7 Mb
Release : 2020-08-04
Category : Computers
ISBN : 9789811224645

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Recommender Systems: Advanced Developments by Jie Lu,Qian Zhang,Guang-quan Zhang Pdf

Recommender systems provide users (businesses or individuals) with personalized online recommendations of products or information, to address the problem of information overload and improve personalized services. Recent successful applications of recommender systems are providing solutions to transform online services for e-government, e-business, e-commerce, e-shopping, e-library, e-learning, e-tourism, and more.This unique compendium not only describes theoretical research but also reports on new application developments, prototypes, and real-world case studies of recommender systems. The comprehensive volume provides readers with a timely snapshot of how new recommendation methods and algorithms can overcome challenging issues. Furthermore, the monograph systematically presents three dimensions of recommender systems — basic recommender system concepts, advanced recommender system methods, and real-world recommender system applications.By providing state-of-the-art knowledge, this excellent reference text will immensely benefit researchers, managers, and professionals in business, government, and education to understand the concepts, methods, algorithms and application developments in recommender systems.

Recommender System with Machine Learning and Artificial Intelligence

Author : Sachi Nandan Mohanty,Jyotir Moy Chatterjee,Sarika Jain,Ahmed A. Elngar,Priya Gupta
Publisher : John Wiley & Sons
Page : 448 pages
File Size : 42,8 Mb
Release : 2020-07-08
Category : Computers
ISBN : 9781119711575

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Recommender System with Machine Learning and Artificial Intelligence by Sachi Nandan Mohanty,Jyotir Moy Chatterjee,Sarika Jain,Ahmed A. Elngar,Priya Gupta Pdf

This book is a multi-disciplinary effort that involves world-wide experts from diverse fields, such as artificial intelligence, human computer interaction, information technology, data mining, statistics, adaptive user interfaces, decision support systems, marketing, and consumer behavior. It comprehensively covers the topic of recommender systems, which provide personalized recommendations of items or services to the new users based on their past behavior. Recommender system methods have been adapted to diverse applications including social networking, movie recommendation, query log mining, news recommendations, and computational advertising. This book synthesizes both fundamental and advanced topics of a research area that has now reached maturity. Recommendations in agricultural or healthcare domains and contexts, the context of a recommendation can be viewed as important side information that affects the recommendation goals. Different types of context such as temporal data, spatial data, social data, tagging data, and trustworthiness are explored. This book illustrates how this technology can support the user in decision-making, planning and purchasing processes in agricultural & healthcare sectors.

Recommendation and Search in Social Networks

Author : Özgür Ulusoy,Abdullah Uz Tansel,Erol Arkun
Publisher : Springer
Page : 289 pages
File Size : 51,7 Mb
Release : 2015-02-12
Category : Computers
ISBN : 9783319143798

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Recommendation and Search in Social Networks by Özgür Ulusoy,Abdullah Uz Tansel,Erol Arkun Pdf

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.

International Symposium on Distributed Computing and Artificial Intelligence 2008 (DCAI ́08)

Author : Juan Manuel Corchado Rodríguez,Sara Rodriguez,James Llinas,Jose M. Molina
Publisher : Springer Science & Business Media
Page : 778 pages
File Size : 40,6 Mb
Release : 2008-09-16
Category : Computers
ISBN : 9783540858638

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International Symposium on Distributed Computing and Artificial Intelligence 2008 (DCAI ́08) by Juan Manuel Corchado Rodríguez,Sara Rodriguez,James Llinas,Jose M. Molina Pdf

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.

Social Networks Science: Design, Implementation, Security, and Challenges

Author : Nilanjan Dey,Rosalina Babo,Amira S. Ashour,Vishal Bhatnagar,Med Salim Bouhlel
Publisher : Springer
Page : 171 pages
File Size : 48,6 Mb
Release : 2018-06-18
Category : Computers
ISBN : 9783319900599

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Social Networks Science: Design, Implementation, Security, and Challenges by Nilanjan Dey,Rosalina Babo,Amira S. Ashour,Vishal Bhatnagar,Med Salim Bouhlel Pdf

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.

Learning Automata Approach for Social Networks

Author : Alireza Rezvanian,Behnaz Moradabadi,Mina Ghavipour,Mohammad Mehdi Daliri Khomami,Mohammad Reza Meybodi
Publisher : Springer
Page : 329 pages
File Size : 52,5 Mb
Release : 2019-01-22
Category : Technology & Engineering
ISBN : 9783030107673

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Learning Automata Approach for Social Networks by Alireza Rezvanian,Behnaz Moradabadi,Mina Ghavipour,Mohammad Mehdi Daliri Khomami,Mohammad Reza Meybodi Pdf

This book begins by briefly explaining learning automata (LA) models and a recently developed cellular learning automaton (CLA) named wavefront CLA. Analyzing social networks is increasingly important, so as to identify behavioral patterns in interactions among individuals and in the networks’ evolution, and to develop the algorithms required for meaningful analysis. As an emerging artificial intelligence research area, learning automata (LA) has already had a significant impact in many areas of social networks. Here, the research areas related to learning and social networks are addressed from bibliometric and network analysis perspectives. In turn, the second part of the book highlights a range of LA-based applications addressing social network problems, from network sampling, community detection, link prediction, and trust management, to recommender systems and finally influence maximization. Given its scope, the book offers a valuable guide for all researchers whose work involves reinforcement learning, social networks and/or artificial intelligence.

Recommender Systems and the Social Web

Author : Fatih Gedikli
Publisher : Springer Science & Business Media
Page : 118 pages
File Size : 44,9 Mb
Release : 2013-03-29
Category : Computers
ISBN : 9783658019488

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Recommender Systems and the Social Web by Fatih Gedikli Pdf

​There is an increasing demand for recommender systems due to the information overload users are facing on the Web. The goal of a recommender system is to provide personalized recommendations of products or services to users. With the advent of the Social Web, user-generated content has enriched the social dimension of the Web. As user-provided content data also tells us something about the user, one can learn the user’s individual preferences from the Social Web. This opens up completely new opportunities and challenges for recommender systems research. Fatih Gedikli deals with the question of how user-provided tagging data can be used to build better recommender systems. A tag recommender algorithm is proposed which recommends tags for users to annotate their favorite online resources. The author also proposes algorithms which exploit the user-provided tagging data and produce more accurate recommendations. On the basis of this idea, he shows how tags can be used to explain to the user the automatically generated recommendations in a clear and intuitively understandable form. With his book, Fatih Gedikli gives us an outlook on the next generation of recommendation systems in the Social Web sphere.

Big Data and Social Media Analytics

Author : Mehmet Çakırtaş,Mehmet Kemal Ozdemir
Publisher : Springer Nature
Page : 246 pages
File Size : 43,8 Mb
Release : 2021-07-05
Category : Mathematics
ISBN : 9783030670443

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Big Data and Social Media Analytics by Mehmet Çakırtaş,Mehmet Kemal Ozdemir Pdf

This edited book provides techniques which address various aspects of big data collection and analysis from social media platforms and beyond. It covers efficient compression of large networks, link prediction in hashtag graphs, visual exploration of social media data, identifying motifs in multivariate data, social media surveillance to enhance search and rescue missions, recommenders for collaborative filtering and safe travel plans to high risk destinations, analysis of cyber influence campaigns on YouTube, impact of location on business rating, bibliographical and co-authorship network analysis, and blog data analytics. All these trending topics form a major part of the state of the art in social media and big data analytics. Thus, this edited book may be considered as a valuable source for readers interested in grasping some of the most recent advancements in this high trending domain.