An Image-based Recommender System Based on Image Annotation

Yıl 2019, Cilt: 3 Sayı: 1, 12 - 16, 27.06.2019

Kemal Özkan Zühal Kurt Erol Seke

Öz

Recommender system is a software that analyzes available data to make recommendations about various
products and services to their users might be interested in.
These systems must perform efficient  for
both users and the e-commerce sites benefiting 
from such systems. Ensuring proper and reliable recommendations
increases user satisfaction that results selling more products and services. Collaborative
filtering, content-based, and hybrid techniques are type of methods for recommender
systems. Content-based recommender systems are usually text-based systems, but
image-based recommender systems have become increasingly in favour for the content-based recommender
systems in recent years.   

The process of an image based recommender system is
to match a users’ image with the most similar image and recommend it. The
recommendation images are the most likely images uploaded and widely acclaimed
from the users. The most challenging problem in image-based recommneder systems
is to match an image with the most similar visual words or classes based on the
image’s visual content.  In this study,
we are planning to solve this problem using Bag of words model, which is an
effective model in computer vision, and also features are extracted with
commonly used descriptors.

Anahtar Kelimeler

Bag of words model, descriptor, cosine similarity, Image-based recommender system

Kaynakça

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