Recommender systems (RS) play a crucial role in aiding decision-making by filtering
information and reducing information overload. Multiple approaches such as collaborative …

Recommender Systems are useful information filtering tools that have reduced information
overload over the web. Collaborative filtering (CF) is one of the extensively used …

Sentiment Analysis (SA) is one of the prominent and emerging research area in the domain
of natural language processing. This paper explores the field of sentiment analysis using …

This paper introduces a novel approach to optimize genetic algorithms (GAs) for homestay
recommendation systems, specifically designed for smart village tourism destinations …

The steady increase in droughts worldwide has compelled many researchers to focus on
water allocation. Multi-objective decision support for irrigation systems is a popular topic due …

In the current landscape, textile companies need rapid, precise, and personalized
assistance, especially as digitalization and information, such as e-commerce and websites …

Represented by evolutionary algorithms and swarm intelligence algorithms, nature-inspired
metaheuristics have been successfully applied to recommender systems and amply …

Herd effect is a widespread phenomenon in real-world situations. This study explores how
the herd effect can be used to manage network flow effectively. We examined its impact on …

This paper introduces CAMCMusic, a novel context-aware multi-criteria music
recommendation system designed to address these limitations without relying on user …

India, known for its agricultural landscape, is a prominent producer of numerous crops
globally. Despite being at the center of the agricultural industry, Indian farmers are often …