Title
Recommender Systems: An Introduction,Used
Sold by Ergodebooks, an authorized reseller.
Returns accepted within 30 days | support@ergodebooks.com
Shipping Information
- Free Standard Shipping — United States only
- Processing Time: 1–3 business days
- Estimated Delivery: 3–5 business days after dispatch
- Double-boxed, fully insured & discreetly packaged
- Tracking number sent via email once dispatched
- Orders over $250 require signature upon delivery. Taxes calculated at checkout.
Returns & Refund
Returns accepted within 30 days of delivery.
Damaged or Defective Item
Free return shipping + replacement or full refund
Wrong Item Received
Free return shipping + replacement or full refund
Change of Mind
Return shipping at customer's expense · 25% restocking fee applies
Payment Option
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 highquality recommendations. This book offers an overview of approaches to developing stateoftheart recommender systems. The authors present current algorithmic approaches for generating personalized buying proposals, such as collaborative and contentbased filtering, as well as more interactive and knowledgebased 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 realworld recommender systems.
⚠️ WARNING (California Proposition 65):
This product may contain chemicals known to the State of California to cause cancer, birth defects, or other reproductive harm.
For more information, please visit www.P65Warnings.ca.gov.
- Q: What is the page count of this book? A: This book has three hundred fifty-two pages. It's a comprehensive read for those interested in recommender systems.
- Q: What type of binding does this book have? A: This book is bound in hardcover. This ensures durability and a professional appearance.
- Q: What are the dimensions of this book? A: The book measures six point two six inches in length, zero point nine eight inches in width, and nine point zero two inches in height.
- Q: How do I use this book effectively? A: Read through the chapters sequentially for a structured understanding. Take notes on key algorithmic approaches and case studies presented.
- Q: Is this book suitable for beginners? A: Yes, the book is suitable for beginners as it provides an overview of recommender systems and their applications.
- Q: What audience is this book intended for? A: This book is intended for computer science researchers, students, and professionals interested in recommender systems.
- Q: How should I store this book? A: Store this book upright on a shelf to prevent warping. Keep it in a dry place to avoid moisture damage.
- Q: Can I clean the cover of this book? A: Yes, you can wipe the cover with a soft, dry cloth. Avoid using any liquids to prevent damage to the binding.
- Q: Does this book contain a glossary of terms? A: No, this book does not contain a specific glossary. However, it explains key terms within the text.
- Q: What topics are covered in this book? A: The book covers algorithmic approaches like collaborative filtering and knowledge-based methods, along with case studies.
- Q: Is there a warranty or return policy for this book? A: Typically, books do not come with a warranty, but check the retailer's return policy for specifics.
- Q: What if the book arrives damaged? A: If the book arrives damaged, contact the retailer for a return or replacement as per their policy.
- Q: How can I measure the effectiveness of recommender systems discussed in this book? A: The book discusses various methods to measure effectiveness, including user satisfaction and recommendation accuracy.
- Q: Are there case studies included in the book? A: Yes, the book includes practical case studies to illustrate the methods discussed.
- Q: What is the author's background? A: The author, Dietmar Jannach, is a recognized expert in recommender systems and has extensive experience in the field.
- Q: What is the main focus of this book? A: The main focus is on developing state-of-the-art recommender systems that provide personalized recommendations.