TY  - BOOK
AU  - Ubalu,Nwabueze Calistus
AU  - Çelebi,Erbuğ
TI  - PRODUCT RECOMMENDATION SYSTEMS
PY  - 2023///
KW  -  Filters and filtration
KW  - Dissertations, Academic
KW  -  Singular value decomposition
N1  - Thesis (MSc) - Cyprus International University. Institute of Graduate Studies and Research Information Systems Engineering Department; Includes bibliography (sheets 51-54)
N2  - ABSTRACT
Accessibility to the web is a per-requisite for every e-commerce website to maintain 
and retain its business in today’s business world. Web users devote interests in surfing 
the net which has made abundant information available for data mining. This data can 
be examined to reveal a lot of patterns that would help users to find their choice of 
pages or products as the case may be. For this to be successful, enhanced mining 
technique background are required to fully extract, comprehend and interpret these 
data. To assist users of e-commerce websites to finding products and resources of their 
choice, an automated approach is required to recommend products or resources to 
users to lessen the time spent on shopping. Well-known companies have employed 
recommendation system to their websites to easy the stress and time spent by users 
which as well have added more benefits to the enterprise. In this research, we have 
discussed collaborative, content-based and hybrid methods of recommendation 
system. Challenges of the existing systems and their various advantages were also 
elaborated. The objective of the research is to recommend relevant products to 
customers as irrelevant products serves as disruption during shopping. In our hybrid 
method of recommendation, we have recommended five top products to a user using 
dataset from Amazon electronic product review and the performance of these models 
were also evaluated.
Keywords: Collaborative filtering, Hybrid filtering, Product-based recommendation, 
Singular Value Decomposition
ER  -