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Recommendation Systems for E-Commerce

  • Couverture cartonnée
  • 136 Nombre de pages
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Nowadays, Recommendation Systems are becoming increasingly vital to the Web users to identify products, services or contents that ... Lire la suite
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Description

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.

Auteur

Hamed Hakimian is currently a researcher in the fields of Business Intelligence, E-Commerce, Information Systems and Recommendation Systems. He received his bachelor's degree in Business Information System from Staffordshire University in 2015.

Informations sur le produit

Titre: Recommendation Systems for E-Commerce
Auteur:
Code EAN: 9783659672750
ISBN: 978-3-659-67275-0
Format: Couverture cartonnée
Editeur: LAP Lambert Academic Publishing
Genre: Informatique
nombre de pages: 136
Poids: 197g
Taille: H7mm x B220mm x T150mm
Année: 2015