Recommendation Systems for E-Commerce

Autor*innen

• Hamed Hakimian

Parameter

• Informatik & Programmierung
• Technik & Maschinenbau

Mehr zum Buch

Nowadays, Recommendation Systems are becoming increasingly vital to the Web users to identify products, services or contents that they might like. Recommendation Systems using Collaborative Filtering are very vulnerable to the Cold-Start problem because they operate solely on the basis of users' preferences. Hence, researches have recently proposed efficient hybrid solutions, so called "Hybrid Recommendation Systems," that combine both Content-based Filtering and Collaborative Filtering to boost the performance. This book attempts to resolve the Cold-Start problem along with implementing a web application working based on information of users' profiles. Finally, to do business analysis, the results of questionnaires and interviews have been brought.

• Sprache: Englisch
• Erscheinungsdatum: 2015
• Einband: Paperback