INTELLIGENT MODEL FOR IMAGE-BASED RECOMMENDATION SYSTEM
Author
Prateek, Prerna
Abstract
Online shopping has developed in parallel with the Internet, and Recommendation Systems have played a pivotal role in its growth. The recommendations are usually provided in two ways: Content-based Filtering and Collaborative Filtering. Both forms of recommendations face the problem of Cold-Start due to an initial lack of information. To overcome this issue, Image-based Recommendation Systems are introduced in order to allow the users to locate products based on similarity of images when purchasing products in categories such as: clothes, shoes, home-decor, kitchen and dining utilities, jewelry, and accessories by mostly viewing images. In this thesis, a Hybrid Model of displaying similar images to that of the product being viewed was developed using Deep Features and Description-based Models. The Hybrid Model displayed a set composed of all images that belong to both Deep Features and Description-based Models. Implementation and comparison of results were performed on 100,000 images of SBU Captioned Photo Dataset.
Subject
Date
2016-08-29
Citation:
APA:
Prateek, Prerna.
(August 2016).
INTELLIGENT MODEL FOR IMAGE-BASED RECOMMENDATION SYSTEM
(Master's Thesis, East Carolina University). Retrieved from the Scholarship.
(http://hdl.handle.net/10342/6004.)
MLA:
Prateek, Prerna.
INTELLIGENT MODEL FOR IMAGE-BASED RECOMMENDATION SYSTEM.
Master's Thesis. East Carolina University,
August 2016. The Scholarship.
http://hdl.handle.net/10342/6004.
September 21, 2023.
Chicago:
Prateek, Prerna,
“INTELLIGENT MODEL FOR IMAGE-BASED RECOMMENDATION SYSTEM”
(Master's Thesis., East Carolina University,
August 2016).
AMA:
Prateek, Prerna.
INTELLIGENT MODEL FOR IMAGE-BASED RECOMMENDATION SYSTEM
[Master's Thesis]. Greenville, NC: East Carolina University;
August 2016.
Collections
Publisher
East Carolina University