Collaborative Recommendations: Algorithms, Practical Challenges And Applications


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.




Collaborative Filtering Recommender Systems


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.




Soft Computing for Problem Solving


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.




The Collaborative Way


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.




The Adaptive Web


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.




Collaborative Assessment


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.




Recommender Systems


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.




What's Mine Is Yours


Book Description

“Amidst a thousand tirades against the excesses and waste of consumer society, What’s Mine Is Yours offers us something genuinely new and invigorating: a way out.” —Steven Johnson, author of The Invention of Air and The Ghost Map A groundbreaking and original book, What’s Mine is Yours articulates for the first time the roots of "collaborative consumption," Rachel Botsman and Roo Roger's timely new coinage for the technology-based peer communities that are transforming the traditional landscape of business, consumerism, and the way we live. Readers captivated by Chris Anderson’s The Long Tail, Van Jones’ The Green Collar Economy or Malcolm Gladwell’s The Tipping Point will be wowed by this landmark contribution to the evolving ecology of commerce and sustainability.




Collaborative Intelligence


Book Description

A breakthrough book on the transformative power of collaborative thinking Collaborative intelligence, or CQ, is a measure of our ability to think with others on behalf of what matters to us all. It is emerging as a new professional currency at a time when the way we think, interact, and innovate is shifting. In the past, “market share” companies ruled by hierarchy and topdown leadership. Today, the new market leaders are “mind share” companies, where influence is more important than power, and success relies on collaboration and the ability to inspire. Collaborative Intelligence is the culmination of more than fifty years of original research that draws on Dawna Markova’s background in cognitive neuroscience and her most recent work, with Angie McArthur, as a “Professional Thinking Partner” to some of the world’s top CEOs and creative professionals. Markova and McArthur are experts at getting brilliant yet difficult people to think together. They have been brought in to troubleshoot for Fortune 500 leaders in crisis and managers struggling to inspire their teams. When asked about their biggest challenges at work, Markova and McArthur’s clients all cite a common problem: other people. This response reflects the way we have been taught to focus on the gulfs between us rather than valuing our intellectual diversity—that is, the ways in which each of us is uniquely gifted, how we process information and frame questions, what kind of things deplete us, and what engages and inspires us. Through a series of practices and strategies, the authors teach us how to recognize our own mind patterns and map the talents of our teams, with the goal of embarking together on an aligned course of action and influence. In Markova and McArthur’s experience, managers who appreciate intellectual diversity will lead their teams to innovation; employees who understand it will thrive because they are in touch with their strengths; and an entire team who understands it will come together to do their best work in a symphony of collaboration, their individual strengths working in harmony like an orchestra or a high-performing sports team. Praise for Collaborative Intelligence “Rooted in the latest neuroscience on the nature of collaboration, Collaborative Intelligence celebrates the power of working and thinking together at the highest levels of business and politics, and in the smallest aspects of our everyday lives. Dawna Markova and Angie McArthur show us that our ability to collaborate is not only a measure of intelligence, but essential to solving the world’s problems and seeing the possibilities in ourselves and others.”—Arianna Huffington “This inspiring book teaches you how to align your intention with the intention of others, and how, through shared strengths and talents, you have every right to expect greatness and set the highest goals and expectations.”—Deepak Chopra “Everyone talks about collaboration today, but the rhetoric typically outweighs the reality. Collaborative Intelligence offers tangible tools for those serious about becoming ‘system leaders’ who can close the gap and make collaboration real.”—Peter M. Senge, author of The Fifth Discipline “I have worked with Markova and McArthur for several years, focusing on achieving better results through intellectual diversity. Their approach has encouraged more candid debate and collaborative behavior within the team. The team, not individuals, becomes the hero.”—Al Carey, CEO, PepsiCo




Deep Learning for Coders with fastai and PyTorch


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