Recommender Systems For Social Tagging Systems
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Recommender Systems For Social Tagging Systems
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Author : Leandro Balby Marinho
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-02-10
Recommender Systems For Social Tagging Systems written by Leandro Balby Marinho and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-02-10 with Computers categories.
Social Tagging Systems are web applications in which users upload resources (e.g., bookmarks, videos, photos, etc.) and annotate it with a list of freely chosen keywords called tags. This is a grassroots approach to organize a site and help users to find the resources they are interested in. Social tagging systems are open and inherently social; features that have been proven to encourage participation. However, with the large popularity of these systems and the increasing amount of user-contributed content, information overload rapidly becomes an issue. Recommender Systems are well known applications for increasing the level of relevant content over the “noise” that continuously grows as more and more content becomes available online. In social tagging systems, however, we face new challenges. While in classic recommender systems the mode of recommendation is basically the resource, in social tagging systems there are three possible modes of recommendation: users, resources, or tags. Therefore suitable methods that properly exploit the different dimensions of social tagging systems data are needed. In this book, we survey the most recent and state-of-the-art work about a whole new generation of recommender systems built to serve social tagging systems. The book is divided into self-contained chapters covering the background material on social tagging systems and recommender systems to the more advanced techniques like the ones based on tensor factorization and graph-based models.
Recommender Systems And The Social Web
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Author : Fatih Gedikli
language : en
Publisher:
Release Date : 2013-04-30
Recommender Systems And The Social Web written by Fatih Gedikli and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-04-30 with categories.
Recommendation And Search In Social Networks
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Author : Özgür Ulusoy
language : en
Publisher: Springer
Release Date : 2015-02-12
Recommendation And Search In Social Networks written by Özgür Ulusoy and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-02-12 with Computers categories.
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.
Recommender Systems For Location Based Social Networks
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Author : Panagiotis Symeonidis
language : en
Publisher: Springer Science & Business Media
Release Date : 2014-02-08
Recommender Systems For Location Based Social Networks written by Panagiotis Symeonidis and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-02-08 with Computers categories.
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.
Formal Concept Analysis And Tag Recommendations In Collaborative Tagging Systems
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Author : Robert Jäschke
language : en
Publisher: Ios PressInc
Release Date : 2011-01-01
Formal Concept Analysis And Tag Recommendations In Collaborative Tagging Systems written by Robert Jäschke and has been published by Ios PressInc this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-01-01 with Computers categories.
One of the most noticeable innovation that emerged with the advent of the Web 2.0 and the focal point of this thesis are collaborative tagging systems. They allow users to annotate arbitrary resources with freely chosen keywords, so called tags. The tags
Recommender Systems For The Social Web
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Author : José J. Pazos Arias
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-01-24
Recommender Systems For The Social Web written by José J. Pazos Arias and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-01-24 with Technology & Engineering categories.
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.
Using Data Mining For Facilitating User Contributions In The Social Semantic Web
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Author : Maryam Ramezani
language : en
Publisher: GRIN Verlag
Release Date : 2011-11-04
Using Data Mining For Facilitating User Contributions In The Social Semantic Web written by Maryam Ramezani and has been published by GRIN Verlag this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-11-04 with Computers categories.
Doctoral Thesis / Dissertation from the year 2011 in the subject Computer Science - Internet, New Technologies, grade: 1,0, Karlsruhe Institute of Technology (KIT), language: English, abstract: Social Web applications have emerged as powerful applications for Internet users allowing them to freely contribute to the Web content, organize and share information, and utilize the collective knowledge of others for discovering new topics, resources and new friends. While social Web applications such as social tagging systems have many benefits, they also present several challenges due to their open and adaptive nature. The amount of user generated data can be extremely large and since there is not any controlled vocabulary or hierarchy, it can be very difficult for users to find the information that is of their interest. In addition, attackers may attempt to distort the system’s adaptive behavior by inserting erroneous or misleading annotations, thus altering the way in which information is presented to legitimate users. This thesis utilizes data mining and machine learning techniques to address these problems. In particular, we design and develop recommender systems to aid the user in contributing to the Social Semantic Web. In addition, we study intelligent techniques to combat attacks against social tagging systems. In our work, we first propose a framework that maps domain properties to recommendation technologies. This framework provides a systematic approach to find the appropriate recommendation technology for addressing a given problem in a specific domain. Second, we improve existing graph-based approaches for personalized tag recommendation in folksonomies. Third, we develop machine learning algorithms for recommendation of semantic relations to support continuous ontology development in a social semanticWeb environment. Finally, we introduce a framework to analyze different types of potential attacks against social tagging systems and evaluate their impact on those systems.
Recommender Systems And The Social Web
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Author : Fatih Gedikli
language : en
Publisher: Springer Vieweg
Release Date : 2013-04-10
Recommender Systems And The Social Web written by Fatih Gedikli and has been published by Springer Vieweg this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-04-10 with Computers categories.
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.
Recommender Systems
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Author : Charu C. Aggarwal
language : en
Publisher: Springer
Release Date : 2016-03-28
Recommender Systems written by Charu C. Aggarwal and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-03-28 with Computers categories.
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.
Social Network Based Recommender Systems
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Author : Daniel Schall
language : en
Publisher: Springer
Release Date : 2015-09-23
Social Network Based Recommender Systems written by Daniel Schall and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-09-23 with Computers categories.
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.