Context-Aware Collaborative Prediction PDF Download

Author: Shu Wu
Publisher: Springer
ISBN: 9811053731
Category : Computers
Languages : en
Pages : 74

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Book Description
This book presents two collaborative prediction approaches based on contextual representation and hierarchical representation, and their applications including context-aware recommendation, latent collaborative retrieval and click-through rate prediction. The proposed techniques offer significant improvements over current methods, the key determinants being the incorporated contextual representation and hierarchical representation. To provide a background to the core ideas presented, it offers an overview of contextual modeling and the theory of contextual representation and hierarchical representation, which are constructed for the joint interaction of entities and contextual information. The book offers a rich blend of theory and practice, making it a valuable resource for students, researchers and practitioners who need to construct systems of information retrieval, data mining and recommendation systems with contextual information.

Author: Fu Lee Wang
Publisher: Springer Nature
ISBN: 3030428354
Category : Computers
Languages : en
Pages : 207

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Book Description
This book constitutes the refereed proceedings of the 15th Information Retrieval Technology Conference, AIRS 2019, held in Hong Kong, China, in November 2019.The 14 full papers presented together with 3 short papers were carefully reviewed and selected from 27 submissions. The scope of the conference covers applications, systems, technologies and theory aspects of information retrieval in text, audio, image, video and multimedia data.

Author: Pavel Brazdil
Publisher: Springer Science & Business Media
ISBN: 3540732624
Category : Computers
Languages : en
Pages : 182

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Book Description
Metalearning is the study of principled methods that exploit metaknowledge to obtain efficient models and solutions by adapting machine learning and data mining processes. While the variety of machine learning and data mining techniques now available can, in principle, provide good model solutions, a methodology is still needed to guide the search for the most appropriate model in an efficient way. Metalearning provides one such methodology that allows systems to become more effective through experience. This book discusses several approaches to obtaining knowledge concerning the performance of machine learning and data mining algorithms. It shows how this knowledge can be reused to select, combine, compose and adapt both algorithms and models to yield faster, more effective solutions to data mining problems. It can thus help developers improve their algorithms and also develop learning systems that can improve themselves. The book will be of interest to researchers and graduate students in the areas of machine learning, data mining and artificial intelligence.

Author: Alexandros Karatzoglou
Publisher:
ISBN: 9781450347952
Category : Computer science
Languages : en
Pages : 47

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Book Description
Workshop on Deep Learning for Recommender Systems Sep 15, 2016-Sep 15, 2016 Boston, USA. You can view more information about this proceeding and all of ACM�s other published conference proceedings from the ACM Digital Library: http://www.acm.org/dl.

Author: Jianxin Li
Publisher: Springer Nature
ISBN: 3030352315
Category : Computers
Languages : en
Pages : 894

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Book Description
This book constitutes the proceedings of the 15th International Conference on Advanced Data Mining and Applications, ADMA 2019, held in Dalian, China in November 2019. The 39 full papers presented together with 26 short papers and 2 demo papers were carefully reviewed and selected from 170 submissions. The papers were organized in topical sections named: Data Mining Foundations; Classification and Clustering Methods; Recommender Systems; Social Network and Social Media; Behavior Modeling and User Profiling; Text and Multimedia Mining; Spatial-Temporal Data; Medical and Healthcare Data/Decision Analytics; and Other Applications.

Author: George A. Papadopoulos
Publisher: Springer Nature
ISBN: 3031462351
Category : Computers
Languages : en
Pages : 295

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Book Description
This book constitutes the constitutes the refereed proceedings of the 10th IFIP WG 6.12 European Conference on Service-Oriented and Cloud Computing , ESOCC 2023, held in Larnaca, Cyprus, during October 24–26, 2023. The 12 full papers and 4 short papers included in this book were carefully reviewed and selected from 40 submissions. They were organized in topical sections as follows: Microservices; Quality of Service; Service Orchestration; Edge Computing; PhD Symposium; and Industry Projects Track.

Author: Francesco Ricci
Publisher: Springer
ISBN: 148997637X
Category : Computers
Languages : en
Pages : 1008

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Book Description
This second edition of a well-received text, with 20 new chapters, presents a coherent and unified repository of recommender systems’ major concepts, theories, methodologies, trends, and challenges. A variety of real-world applications and detailed case studies are included. In addition to wholesale revision of the existing chapters, this edition includes new topics including: decision making and recommender systems, reciprocal recommender systems, recommender systems in social networks, mobile recommender systems, explanations for recommender systems, music recommender systems, cross-domain recommendations, privacy in recommender systems, and semantic-based recommender systems. This multi-disciplinary handbook involves world-wide experts from diverse fields such as artificial intelligence, human-computer interaction, information retrieval, data mining, mathematics, statistics, adaptive user interfaces, decision support systems, psychology, marketing, and consumer behavior. Theoreticians and practitioners from these fields will find this reference to be an invaluable source of ideas, methods and techniques for developing more efficient, cost-effective and accurate recommender systems.

Author: Shangguang Wang
Publisher: Springer
ISBN: 3319592882
Category : Computers
Languages : en
Pages : 706

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Book Description
This book constitutes the thoroughly refereed proceedings of the 12th International Conference on Collaborative Computing: Networking, Applications, and Worksharing, CollaborateCom 2016, held in Beijing, China, in November 2016. The 66 papers presented were carefully reviewed and selected from 116 submissions and focus on topics such as: participatory sensing, crowdsourcing, and citizen science; architectures, protocols, and enabling technologies for collaborative computing networks and systems; autonomic computing and quality of services in collaborative networks, systems, and applications; collaboration in pervasive and cloud computing environments; collaboration in data-intensive scientific discovery; collaboration in social media; big data and spatio-temporal data in collaborative environments/systems; collaboration techniques in data-intensive computing and cloud computing.

Author: Sami Yangui
Publisher: Springer Nature
ISBN: 3030337022
Category : Computers
Languages : en
Pages : 593

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Book Description
This book constitutes the proceedings of the 17th International Conference on Service-Oriented Computing, ICSOC 2019, held in Toulouse, France, in October 2019. The 28 full and 12 short papers presented together with 7 poster and 2 invited papers in this volume were carefully reviewed and selected from 181 submissions. The papers have been organized in the following topical sections: Service Engineering; Run-time Service Operations and Management; Services and Data; Services in the Cloud; Services on the Internet of Things; Services in Organizations, Business and Society; and Services at the Edge.

Author: Charu C. Aggarwal
Publisher: Springer
ISBN: 3319296590
Category : Computers
Languages : en
Pages : 518

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Book Description
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.