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Author: Francesco Ricci
Publisher: Springer Nature
ISBN: 1071621971
Category : Computers
Languages : en
Pages : 1053
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Book Description
This third edition handbook describes in detail the classical methods as well as extensions and novel approaches that were more recently introduced within this field. It consists of five parts: general recommendation techniques, special recommendation techniques, value and impact of recommender systems, human computer interaction, and applications. The first part presents the most popular and fundamental techniques currently used for building recommender systems, such as collaborative filtering, semantic-based methods, recommender systems based on implicit feedback, neural networks and context-aware methods. The second part of this handbook introduces more advanced recommendation techniques, such as session-based recommender systems, adversarial machine learning for recommender systems, group recommendation techniques, reciprocal recommenders systems, natural language techniques for recommender systems and cross-domain approaches to recommender systems. The third part covers a wide perspective to the evaluation of recommender systems with papers on methods for evaluating recommender systems, their value and impact, the multi-stakeholder perspective of recommender systems, the analysis of the fairness, novelty and diversity in recommender systems. The fourth part contains a few chapters on the human computer dimension of recommender systems, with research on the role of explanation, the user personality and how to effectively support individual and group decision with recommender systems. The last part focusses on application in several important areas, such as, food, music, fashion and multimedia recommendation. This informative third edition handbook provides a comprehensive, yet concise and convenient reference source to recommender systems for researchers and advanced-level students focused on computer science and data science. Professionals working in data analytics that are using recommendation and personalization techniques will also find this handbook a useful tool.
Author: Francesco Ricci
Publisher: Springer Nature
ISBN: 1071621971
Category : Computers
Languages : en
Pages : 1053
Get Book Here
Book Description
This third edition handbook describes in detail the classical methods as well as extensions and novel approaches that were more recently introduced within this field. It consists of five parts: general recommendation techniques, special recommendation techniques, value and impact of recommender systems, human computer interaction, and applications. The first part presents the most popular and fundamental techniques currently used for building recommender systems, such as collaborative filtering, semantic-based methods, recommender systems based on implicit feedback, neural networks and context-aware methods. The second part of this handbook introduces more advanced recommendation techniques, such as session-based recommender systems, adversarial machine learning for recommender systems, group recommendation techniques, reciprocal recommenders systems, natural language techniques for recommender systems and cross-domain approaches to recommender systems. The third part covers a wide perspective to the evaluation of recommender systems with papers on methods for evaluating recommender systems, their value and impact, the multi-stakeholder perspective of recommender systems, the analysis of the fairness, novelty and diversity in recommender systems. The fourth part contains a few chapters on the human computer dimension of recommender systems, with research on the role of explanation, the user personality and how to effectively support individual and group decision with recommender systems. The last part focusses on application in several important areas, such as, food, music, fashion and multimedia recommendation. This informative third edition handbook provides a comprehensive, yet concise and convenient reference source to recommender systems for researchers and advanced-level students focused on computer science and data science. Professionals working in data analytics that are using recommendation and personalization techniques will also find this handbook a useful tool.
Author: Mehmet Kaya
Publisher: Springer
ISBN: 3319781960
Category : Social Science
Languages : en
Pages : 254
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Book Description
This book is a timely collection of chapters that present the state of the art within the analysis and application of big data. Working within the broader context of big data, this text focuses on the hot topics of social network modelling and analysis such as online dating recommendations, hiring practices, and subscription-type prediction in mobile phone services. Manuscripts are expanded versions of the best papers presented at the IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM’2016), which was held in August 2016. The papers were among the best featured at the meeting and were then improved and extended substantially. Social Network Based Big Data Analysis and Applications will appeal to students and researchers in the field.
Author: Rokia Missaoui
Publisher: Springer
ISBN: 331912188X
Category : Computers
Languages : en
Pages : 282
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Book Description
This book is devoted to recent progress in social network analysis with a high focus on community detection and evolution. The eleven chapters cover the identification of cohesive groups, core components and key players either in static or dynamic networks of different kinds and levels of heterogeneity. Other important topics in social network analysis such as influential detection and maximization, information propagation, user behavior analysis, as well as network modeling and visualization are also presented. Many studies are validated through real social networks such as Twitter. This edited work will appeal to researchers, practitioners and students interested in the latest developments of social network analysis.
Author: Longbing Cao
Publisher: Springer Science & Business Media
ISBN: 3642283195
Category : Computers
Languages : en
Pages : 526
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Book Description
This book constitutes the thoroughly refereed post-conference proceedings of five international workshops held in conjunction with PAKDD 2011 in Shenzhen, China, in May 2011: the International Workshop on Behavior Informatics (BI 2011), the Workshop on Quality Issues, Measures of Interestingness and Evaluation of Data Mining Models (QIMIE 2011), the Workshop on Biologically Inspired Techniques for Data Mining (BDM 2011), the Workshop on Advances and Issues in Traditional Chinese Medicine Clinical Data Mining (AI-TCM 2011), and the Second Workshop on Data Mining for Healthcare Management (DMGHM 2011). The book also includes papers from the First PAKDD Doctoral Symposium on Data Mining (DSDM 2011). The 42 papers were carefully reviewed and selected from numerous submissions. The papers cover a wide range of topics discussing emerging techniques in the field of knowledge discovery in databases and their application domains extending to previously unexplored areas such as data mining based on optimization techniques from biological behavior of animals and applications in Traditional Chinese Medicine clinical research and health care management.
Author:
Publisher:
ISBN: 9781742101842
Category : Recommender systems (Information filtering)
Languages : en
Pages : 8
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Book Description
Author: Ankur A. Patel
Publisher: O'Reilly Media
ISBN: 1492035610
Category : Computers
Languages : en
Pages : 362
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Book Description
Many industry experts consider unsupervised learning the next frontier in artificial intelligence, one that may hold the key to general artificial intelligence. Since the majority of the world's data is unlabeled, conventional supervised learning cannot be applied. Unsupervised learning, on the other hand, can be applied to unlabeled datasets to discover meaningful patterns buried deep in the data, patterns that may be near impossible for humans to uncover. Author Ankur Patel shows you how to apply unsupervised learning using two simple, production-ready Python frameworks: Scikit-learn and TensorFlow using Keras. With code and hands-on examples, data scientists will identify difficult-to-find patterns in data and gain deeper business insight, detect anomalies, perform automatic feature engineering and selection, and generate synthetic datasets. All you need is programming and some machine learning experience to get started. Compare the strengths and weaknesses of the different machine learning approaches: supervised, unsupervised, and reinforcement learning Set up and manage machine learning projects end-to-end Build an anomaly detection system to catch credit card fraud Clusters users into distinct and homogeneous groups Perform semisupervised learning Develop movie recommender systems using restricted Boltzmann machines Generate synthetic images using generative adversarial networks
Author: Julian McAuley
Publisher: Cambridge University Press
ISBN: 1009008579
Category : Computers
Languages : en
Pages : 338
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Book Description
Every day we interact with machine learning systems offering individualized predictions for our entertainment, social connections, purchases, or health. These involve several modalities of data, from sequences of clicks to text, images, and social interactions. This book introduces common principles and methods that underpin the design of personalized predictive models for a variety of settings and modalities. The book begins by revising 'traditional' machine learning models, focusing on adapting them to settings involving user data, then presents techniques based on advanced principles such as matrix factorization, deep learning, and generative modeling, and concludes with a detailed study of the consequences and risks of deploying personalized predictive systems. A series of case studies in domains ranging from e-commerce to health plus hands-on projects and code examples will give readers understanding and experience with large-scale real-world datasets and the ability to design models and systems for a wide range of applications.
Author: Joseph Konstan
Publisher: Springer Science & Business Media
ISBN: 3642223613
Category : Computers
Languages : en
Pages : 480
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Book Description
This book constitutes the proceedings of the third annual conference under the UMAP title, aptation, which resulted from the merger in 2009 of the successful biannual User Modeling (UM) and Adaptive Hypermedia (AH) conference series, held on Girona, Spain, in July 2011. The 27 long papers and 6 short papers presented together with15 doctoral consortium papers, 2 invited talks, and 3 industry panel papers were carefully reviewed and selected from 164 submissions. The tutorials and workshops were organized in topical sections on designing adaptive social applications, semantic adaptive social Web, and designing and evaluating new generation user modeling.
Author: Haoran Xie
Publisher: Springer
ISBN: 3319667335
Category : Education
Languages : en
Pages : 232
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Book Description
This book constitutes the proceedings of the 16th International Conference on Web-Based Learning, ICWL 2017, held in Cape Town, South Africa, in September 2017. The 13 revised full papers presented together with 9 short papers and 3 poster papers were carefully reviewed and selected from 56 submissions. The papers are organized in topical sections on Inquiry-Based Learning and Gamification; Learning Analytics; Social Media and Web 2.0-based Learning Environments; Assessment and Accessibility in Higher Education; Open Educational Resources and Recommender Systems; and Practice and Experience Sharing.
Author: Deana A. Rohlinger
Publisher: Oxford University Press
ISBN: 0197510639
Category : Medical
Languages : en
Pages : 745
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Book Description
Digital media are normal. But this was not always true. For a long time, lay discourse, academic exhortations, pop culture narratives, and advocacy groups constructed new Information and communications technologies (ICTs) as exceptional. Whether they were believed to be revolutionary, dangerous, rife with opportunity, or other-worldly, these tools and technologies were framed as extraordinary. But digital media are now mundane, thoroughly embedded - and often unquestioned - in everyday life. Digital ICTs are enmeshed in health and wellness, work and organizations, elections, capital flows, intimate relationships, social movements, and even our own identities. And although the study of these technologies has always been interdisciplinary - at the crossroads of computer science, cultural studies, science and technology studies, and communications - never has a sociological perspective been more valuable. Sociology has always excelled at helping us re-see the normal. The Oxford Handbook of Digital Media Sociology is a perfect point of entry for those curious about the state of sociological research on digital media. Each chapter reviews the sociological research that has been done thus far and points towards unanswered questions. The 34 chapters in the Handbook are arranged in six sections which look at digital media as they relate to: theory, social institutions, everyday life, community and identity, social inequalities, and politics & power. More than ever, the contributors to this volume help make it a centralizing resource, pulling together the various strands of sociological research focused on digital media. In addition to providing a distinctly sociological center for those scholars looking to find their way in the subfield, the volume offers top sociological research that provides an overview of digital media to explain our quickly changing world to a broader public. Readers will find it accessible enough for use in class, and thorough enough for seasoned professionals interested in a concise update in their areas of interest.
