The Internet has revolutionized the way information is retrieved, and the increase in the
number of users has resulted in a surge in the volume and heterogeneity of available data …

This paper presents a deep architecture for learning a similarity metric on variablelength
character sequences. The model combines a stack of character-level bidirectional LSTM's …

A growing proportion of the global population is becoming overweight or obese, leading to
various diseases (eg, diabetes, ischemic heart disease and even cancer) due to unhealthy …

Nutrient-based meal recommendations have the potential to help individuals prevent or
manage conditions such as diabetes and obesity. However, learning people's food …

The recommendation of food items is important for many reasons. Attaining cooking
inspiration via digital sources is becoming evermore popular; as are systems, which …

Cuisine is a style of cooking and usually associated with a specific geographic region.
Recipes from different cuisines shared on the web are an indicator of culinary cultures in …

Visually-aware food recommendation recommends food items based on their visual
features. Existing methods typically use the pre-extracted visual features from food …

This paper considers the problem of recipe-oriented image-ingredient correlation learning
with multi-attributes for recipe retrieval and exploration. Existing methods mainly focus on …

Food recommender systems play an important role in assisting users to identify the desired
food to eat. Deciding what food to eat is a complex and multi-faceted process, which is …

Recommender Systems help us deal with information overload by suggesting relevant items
based on our personal preferences. Although there is a large body of research in areas such …