Recommendation systems are commonly used to provide consumers with customized
services. They are primarily designed to provide recommendations or ideas that address the …

With restaurant menus becoming vast and dish names complicated, we present a
recommendation system to facilitate ordering food at restaurants. The design approach is …

Deep learning algorithms have been highly successful in various domains, including the
development of collaborative filtering recommender systems. However, one of the …

The rapid growth of e-commerce has caused product overload where customers on the Web
are no longer able to effectively choose the products they are exposed to. To overcome the …

Many deep learning-based recommender systems have been proposed recently. Where
they involve all the users in datasets to build the latent representation of input data to be …

Food is one of the four essential factors, and nowadays, Thai cuisine is highly famous
domestically and internationally. The majority of Thai culinary culture involves preparing and …

Determining the cost of shipping has long been a cornerstone of urban logistics, but today's
effective outcomes need acceptable precision. Around the globe, internet-based meal …

This study presents a mobile food journaling application which offers functionalities to help
users become aware of nutritional content and calories consumed throughout the day. We …

The recommender system is a filtering technique that tries to reduce the available selections
for users by finding the relevant items that satisfy their desires. Collaborative filtering is the …

Recommender system (RS) is a suitable tool for filtering out items and providing the most
relevant and suitable items to each user, based on their individual preferences. Deep …