Collaborative Recommendations: Algorithms, Practical Challenges And Applications PDF Download

Author: Shlomo Berkovsky
Publisher: World Scientific
ISBN: 9813275367
Category : Computers
Languages : en
Pages : 736

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Book Description
Recommender systems are very popular nowadays, as both an academic research field and services provided by numerous companies for e-commerce, multimedia and Web content. Collaborative-based methods have been the focus of recommender systems research for more than two decades.The unique feature of the compendium is the technical details of collaborative recommenders. The book chapters include algorithm implementations, elaborate on practical issues faced when deploying these algorithms in large-scale systems, describe various optimizations and decisions made, and list parameters of the algorithms.This must-have title is a useful reference materials for researchers, IT professionals and those keen to incorporate recommendation technologies into their systems and services.

Author: Michael D. Ekstrand
Publisher: Now Publishers Inc
ISBN: 1601984421
Category : Computers
Languages : en
Pages : 104

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Book Description
Collaborative Filtering Recommender Systems discusses a wide variety of the recommender choices available and their implications, providing both practitioners and researchers with an introduction to the important issues underlying recommenders and current best practices for addressing these issues.

Author: Kedar Nath Das
Publisher: Springer Nature
ISBN: 981150184X
Category : Technology & Engineering
Languages : en
Pages : 980

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Book Description
This two-volume book presents the outcomes of the 8th International Conference on Soft Computing for Problem Solving, SocProS 2018. This conference was a joint technical collaboration between the Soft Computing Research Society, Liverpool Hope University (UK), and Vellore Institute of Technology (India), and brought together researchers, engineers and practitioners to discuss thought-provoking developments and challenges in order to select potential future directions. The book highlights the latest advances and innovations in the interdisciplinary areas of soft computing, including original research papers on algorithms (artificial immune systems, artificial neural networks, genetic algorithms, genetic programming, and particle swarm optimization) and applications (control systems, data mining and clustering, finance, weather forecasting, game theory, business and forecasting applications). It offers a valuable resource for both young and experienced researchers dealing with complex and intricate real-world problems that are difficult to solve using traditional methods.

Author: Jason Fickett
Publisher:
ISBN:
Category :
Languages : en
Pages : 122

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Book Description
CEO Barry Halton is beginning to think he's not cut out to carry a company from ordinary to extraordinary. After a great start-up, his second company has hit an all-too-familiar wall.Frustrated and discouraged, he runs into an old friend who introduces him to The Collaborative Way(R), a way of working together that not only builds a great place to work but also generates the competitive advantage Barry is looking for.Three years after that chance encounter, the result is a dramatic change in Barry's leadership and in the leadership throughout his company-a tremendous growth in collaboration that's moving the company forward in a powerful and inspiring way.

Author: Peter Brusilovski
Publisher: Springer Science & Business Media
ISBN: 3540720782
Category : Computers
Languages : en
Pages : 770

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Book Description
This state-of-the-art survey provides a systematic overview of the ideas and techniques of the adaptive Web and serves as a central source of information for researchers, practitioners, and students. The volume constitutes a comprehensive and carefully planned collection of chapters that map out the most important areas of the adaptive Web, each solicited from the experts and leaders in the field.

Author: Stephen A. Goodman
Publisher: American Foundation for the Blind
ISBN: 9780891288695
Category : Education
Languages : en
Pages : 460

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Book Description
Collaborative Assessment is designed to help all professionals who work with visually impaired students understand the impact of visual impairment on assessing students' learning potential. Written by the expert assessment team at the California School for the Blind, this book focuses on evaluating students in a variety of areas, including psychology, speech and language, orientation and mobility, and technology, and provides a framework for developing a cooperative, interactive team of professionals from a variety of disciplines to achieve accurate evaluation of the needs and strengths of students. School psychologists, speech and language pathologists, administrators, teachers, and parents will find this book invaluable. Includes helpful forms and checklists and annotated lists of assessments in each area.

Author: Christine Preisach
Publisher: Springer Science & Business Media
ISBN: 354078246X
Category : Computers
Languages : en
Pages : 714

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Book Description
Data analysis and machine learning are research areas at the intersection of computer science, artificial intelligence, mathematics and statistics. They cover general methods and techniques that can be applied to a vast set of applications such as web and text mining, marketing, medical science, bioinformatics and business intelligence. This volume contains the revised versions of selected papers in the field of data analysis, machine learning and applications presented during the 31st Annual Conference of the German Classification Society (Gesellschaft für Klassifikation - GfKl). The conference was held at the Albert-Ludwigs-University in Freiburg, Germany, in March 2007.

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.

Author: Jeremy Howard
Publisher: O'Reilly Media
ISBN: 1492045497
Category : Computers
Languages : en
Pages : 624

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Book Description
Deep learning is often viewed as the exclusive domain of math PhDs and big tech companies. But as this hands-on guide demonstrates, programmers comfortable with Python can achieve impressive results in deep learning with little math background, small amounts of data, and minimal code. How? With fastai, the first library to provide a consistent interface to the most frequently used deep learning applications. Authors Jeremy Howard and Sylvain Gugger, the creators of fastai, show you how to train a model on a wide range of tasks using fastai and PyTorch. You’ll also dive progressively further into deep learning theory to gain a complete understanding of the algorithms behind the scenes. Train models in computer vision, natural language processing, tabular data, and collaborative filtering Learn the latest deep learning techniques that matter most in practice Improve accuracy, speed, and reliability by understanding how deep learning models work Discover how to turn your models into web applications Implement deep learning algorithms from scratch Consider the ethical implications of your work Gain insight from the foreword by PyTorch cofounder, Soumith Chintala

Author: IEEE Staff
Publisher:
ISBN: 9781728126661
Category :
Languages : en
Pages :

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Book Description
electrical and electronic engineering, telecommunications, computer engineering, computer science and allied disciplines as well as those interested in the innovative use of digital technologies for learning, teaching and assessment in any discipline