Recommender Systems (original) (raw)

Show more authors

You may already have access via personal or institutional login

You may already have access via personal or institutional login

In this age of information overload, people use a variety of strategies to make choices about what to buy, how to spend their leisure time, and even whom to date. Recommender systems automate some of these strategies with the goal of providing affordable, personal, and high-quality recommendations. This book offers an overview of approaches to developing state-of-the-art recommender systems. The authors present current algorithmic approaches for generating personalized buying proposals, such as collaborative and content-based filtering, as well as more interactive and knowledge-based approaches. They also discuss how to measure the effectiveness of recommender systems and illustrate the methods with practical case studies. The final chapters cover emerging topics such as recommender systems in the social web and consumer buying behavior theory. Suitable for computer science researchers and students interested in getting an overview of the field, this book will also be useful for professionals looking for the right technology to build real-world recommender systems.

‘Behind the modest title of ‘An Introduction’ lies the type of work the field needs to consolidate its learning and move forward to address new challenges. Across the chapters that follow lie both a tour of what the field knows well - a diverse collection of algorithms and approaches to recommendation - and a snapshot of where the field is today as new approaches derived from social computing and the semantic web find their place in the recommender systems toolbox. Let's all hope this worthy effort spurs yet more creativity and innovation to help recommender systems move forward to new heights.’

Joseph A. Konstan - from the Foreword

Contents

Contents

Select Frontmatter

Select Contents

Select Foreword

Select Preface

Select 1 - Introduction

Select PART I - INTRODUCTION TO BASIC CONCEPTS

Select 2 - Collaborative recommendation

Select 3 - Content-based recommendation

Select 4 - Knowledge-based recommendation

Select 5 - Hybrid recommendation approaches

Select 6 - Explanations in recommender systems

Select 7 - Evaluating recommender systems

Select PART II - RECENT DEVELOPMENTS

Select 10 - Online consumer decision making

Select 13 - Summary and outlook

Select Bibliography

Select Index

Metrics

Altmetric attention score

Full text views

Full text views help

Total number of HTML views: 0

Total number of PDF views: 0 *

Loading metrics...

* Views captured on Cambridge Core between #date#. This data will be updated every 24 hours.

Usage data cannot currently be displayed.

Why this information is here

This section outlines the accessibility features of this content - including support for screen readers, full keyboard navigation and high-contrast display options. This may not be relevant for you.

Accessibility Information

Accessibility compliance for the PDF of this book is currently unknown and may be updated in the future.