Food recommender-systems are considered an effective tool to help users adjust their
eating habits and achieve a healthier diet. This paper aims to develop a new hybrid food …

Similarity is a vital component for neighborhood-based collaborative filtering (CF). To
improve the quality of recommendation, many similarity methods have been proposed and …

This paper proposes a novel integrated model based on multi-criteria decision-making
(MCDM) method to assess and rank the feeder sections to optimally locate fault indicators in …

Typical recommender systems utilize observed ratings of users as inputs to learn their
preferences and aim to output recommendations of new items that users will like by …

The evolution of modern mobile terminals, social networks, and other intelligent services
makes everyone become a ubiquitous information perceiver, producer, and propagator. Also …

Well placement optimization is directly related to the recovery factor of reservoir
development, and at present, the mainstream solution is an evolutionary algorithm …

Recommender systems aim to support users in decision-making through the knowledge
extracted from historical ratings. However, many of these ratings may be noisy and/or …

Cosine similarity between two documents can be computed using token embeddings formed
by Large Language Models (LLMs) such as GPT-4, and used to categorize those documents …

Recommender systems position themselves as powerful tools in the support of relevance
and personalization, presenting remarkable potential in the area of marketing. The cold-start …

Rating prediction is crucial in recommender systems as it enables personalized
recommendations based on different models and techniques, making it of significant …