Recommendation In Social Media
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Spatio Temporal Recommendation In Social Media
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Author : Hongzhi Yin
language : en
Publisher: Springer
Release Date : 2016-05-19
Spatio Temporal Recommendation In Social Media written by Hongzhi Yin and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-05-19 with Computers categories.
This book covers the major fundamentals of and the latest research on next-generation spatio-temporal recommendation systems in social media. It begins by describing the emerging characteristics of social media in the era of mobile internet, and explores the limitations to be found in current recommender techniques. The book subsequently presents a series of latent-class user models to simulate users’ behaviors in decision-making processes, which effectively overcome the challenges arising from temporal dynamics of users’ behaviors, user interest drift over geographical regions, data sparsity and cold start. Based on these well designed user models, the book develops effective multi-dimensional index structures such as Metric-Tree, and proposes efficient top-k retrieval algorithms to accelerate the process of online recommendation and support real-time recommendation. In addition, it offers methodologies and techniques for evaluating both the effectiveness and efficiency of spatio-temporal recommendation systems in social media. The book will appeal to a broad readership, from researchers and developers to undergraduate and graduate students.
Recommendation In Social Media
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Author : Xin Wang
language : en
Publisher:
Release Date : 2017
Recommendation In Social Media written by Xin Wang and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017 with categories.
Recommender systems are ubiquitous in our digital life in recent years. They play a significant role in numerous Internet services and applications such as electronic commerce (Amazon and eBay), on-demand video streaming (Netflix and Hulu). A key task in recommender systems is to model user preferences and to suggest, for each user, a personalized list of items that the user has not experienced, but are deemed highly relevant to her. Many of these recommendation algorithms are based on the principle of collaborative filtering, suggesting items that similar users have consumed. With the advent of online social networks, social recommendation has become one of the most popular research topics in recommender systems, exploiting the effects of social influence and selection in social networks, where user relationships are explicit, i.e., there will be an edge connecting two users if they are friends. In addition, more information about the relationships between users in social media becomes available with the rapid development of various Internet services. For example, more and more online web services are providing mechanisms by which users can self-organize into groups with other users having similar opinions or interests, enabling us to analyze the interactions between users with others insides/outsides groups, as well as the engagement between users and groups. User relationships in these applications are usually implicit and can only be utilized indirectly for recommendation tasks. In this thesis, we focus on utilizing user relationships (either explicit or implicit) to enhance personalized recommendation in social media. We study three problems of recommendation in social media, i.e., recommendation with strong and weak ties, social group recommendation and interactive social recommendation in an online setting. We propose to improve social recommendation by incorporating the concept of strong and weak ties which are two well documented terms in the social sciences, boost the performance of social group recommendation through modeling the temporal dynamics of engagement of users with groups, and tackle the interactive social recommendation problem via employing the exploitation-exploration strategy in an online setting. Our proposed models are all compared with state-of-the-art baselines on several real-world datasets.
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 System With Machine Learning And Artificial Intelligence
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Author : Sachi Nandan Mohanty
language : en
Publisher: John Wiley & Sons
Release Date : 2020-07-08
Recommender System With Machine Learning And Artificial Intelligence written by Sachi Nandan Mohanty and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-07-08 with Computers categories.
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.
Social Information Access
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Author : Peter Brusilovsky
language : en
Publisher: Springer
Release Date : 2018-05-02
Social Information Access written by Peter Brusilovsky and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-05-02 with Computers categories.
Social information access is defined as a stream of research that explores methods for organizing the past interactions of users in a community in order to provide future users with better access to information. Social information access covers a wide range of different technologies and strategies that operate on a different scale, which can range from a small closed corpus site to the whole Web. The 16 chapters included in this book provide a broad overview of modern research on social information access. In order to provide a balanced coverage, these chapters are organized by the main types of information access (i.e., social search, social navigation, and recommendation) and main sources of social information.
On Effective Methods For Social Media Content Analysis And Recommendation
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Author : Cristina Ioana Muntean
language : ro
Publisher:
Release Date : 2012
On Effective Methods For Social Media Content Analysis And Recommendation written by Cristina Ioana Muntean and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012 with categories.
Recommendations In Social Media For Brand Monitoring
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Author : Shanchan Wu
language : en
Publisher:
Release Date : 2012
Recommendations In Social Media For Brand Monitoring written by Shanchan Wu and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012 with categories.
We present a recommendation system for social media that draws upon monitoring and prediction methods. We use historical posts on some focal topic or historical links to a focal blog channel to recommend a set of authors to follow. Such a system would be useful for brand managers interested in monitoring conversations about their products. Our recommendations are based on a prediction system that trains a ranking Support Vector Machine (RSVM) using multiple features including the content of a post, similarity between posts, links between posts and/or blog channels, and links to external websites. We solve two problems, Future Author Prediction (FAP) and Future Link Prediction (FLP), and apply the prediction outcome to make recommendations. Using an extensive experimental evaluation on a blog dataset, we demonstrate the quality and value of our recommendations.
Putting Social Media And Networking Data In Practice For Education Planning Prediction And Recommendation
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Author : Mehmet Kaya
language : en
Publisher: Springer Nature
Release Date : 2019-12-27
Putting Social Media And Networking Data In Practice For Education Planning Prediction And Recommendation written by Mehmet Kaya and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-12-27 with Science categories.
This book focusses on recommendation, behavior, and anomaly, among of social media analysis. First, recommendation is vital for a variety of applications to narrow down the search space and to better guide people towards educated and personalized alternatives. In this context, the book covers supporting students, food venue, friend and paper recommendation to demonstrate the power of social media data analysis. Secondly, this book treats behavior analysis and understanding as important for a variety of applications, including inspiring behavior from discussion platforms, determining user choices, detecting following patterns, crowd behavior modeling for emergency evacuation, tracking community structure, etc. Third, fraud and anomaly detection have been well tackled based on social media analysis. This has is illustrated in this book by identifying anomalous nodes in a network, chasing undetected fraud processes, discovering hidden knowledge, detecting clickbait, etc. With this wide coverage, the book forms a good source for practitioners and researchers, including instructors and students.
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.
On Recommendations In Heterogeneous Social Media Networks
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Author :
language : en
Publisher:
Release Date : 2013
On Recommendations In Heterogeneous Social Media Networks written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013 with categories.