High-Scale Food Recommendation Built on Apache Spark using Alternating Least Squares

Guntupalli, Yashvanth Kumar; Saketh, Vemula Sai; Amudheswaran, S; Vaishnav, Devashish S

doi:10.1109/icraie51050.2020.9358277

Cited by 3 publications

(1 citation statement)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…• Novel algorithm: A newly developed algorithm or method that introduces innovative approaches to solve a specific problem. • ALS Algorithm: Alternating Least Squares Algorithm, a matrix factorization method commonly used in collaborative filtering for recommendation systems [78]. • Group Mutual Recommendation: Group Mutual Recommendation, a method that provides recommendations based on the preferences of groups of users [79].…”

Section: B Data Sparsitymentioning

confidence: 99%

Exploring the Landscape of Hybrid Recommendation Systems in E-Commerce: A Systematic Literature Review

Bodduluri,

Palma,

Kurti

et al. 2024

IEEE Access

View full text Add to dashboard Cite

This article presents a systematic literature review on hybrid recommendation systems (HRS) in the e-commerce sector, a field characterized by constant innovation and rapid growth. As the complexity and volume of digital data increases, recommendation systems have become essential in guiding customers to services or products that align with their interests. However, the effectiveness of singlearchitecture recommendation algorithms is often limited by issues such as data sparsity, challenges in understanding user needs, and the cold start problem. Hybridization, which combines multiple algorithms in different methods, has emerged as a dominant solution to these limitations. This approach is utilized in various domains, including e-commerce, where it significantly improves user experience and sales. To capture the recent trends and advancements in HRS within e-commerce over the past six years, we review the state-of-the-art overview of HRS within e-commerce. This review meticulously evaluates existing research, addressing primary inquiries and presenting findings that contribute to evidence-based decisionmaking, understanding research gaps, and maintaining transparency. The review begins by establishing fundamental concepts, followed by detailed methodologies, findings from addressing the research questions, and exploration of critical aspects of HRS. In summarizing and incorporating existing research, this paper offers valuable insights for researchers and outlines potential avenues for future research, ultimately providing a comprehensive overview of the current state and prospects of HRS in e-commerce.

show abstract

Section: B Data Sparsitymentioning

confidence: 99%