Modeling user rating preference behavior to improve the performance of the collaborative filtering based recommender systems.

One of the main concerns for online shopping websites is to provide efficient and customized recommendations to a very large number of users based on their preferences. Collaborative filtering (CF) is the most famous type of recommender system method to provide personalized recommendations to users. CF generates recommendations by identifying clusters of similar users or items from the user-item rating matrix.

A comprehensive study of mobile-health based assistive technology for the healthcare of dementia and Alzheimer's disease (AD).

Assistive technology (AT) involvement in therapeutic treatment has provided simple and efficient healthcare solutions to people. Within a short span of time, mobile health (mHealth) has grown rapidly for assisting people living with a chronic disorder. This research paper presents the comprehensive study to identify and review existing mHealth dementia applications (apps), and also synthesize the evidence of using these applications in assisting people with dementia including Alzheimer's disease (AD) and their caregivers.

Applying the Concept of Nutrient-Profiling to Promote Healthy Eating and Raise Individuals' Awareness of the Nutritional Quality of their Food.

Diet-related chronic diseases are on the rise. Current dietary management approaches are mostly calorie-counter tools that draw our attention away from the nutritional quality of our food choices. To improve consumers' dietary behavior, we need a simple technique to educate them about nutrition and increase their understanding of the nutritional quality of their food.