Recommendation Systems for E-Commerce - Hakimian, Hamed
30,99 €
inkl. MwSt.
Versandkostenfrei*
Versandfertig in 6-10 Tagen
payback
15 °P sammeln
  • Broschiertes 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…mehr

Andere Kunden interessierten sich auch für
Produktbeschreibung
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.
Autorenporträt
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.