Scalability and sparsity issues in recommender datasets: a survey

2018/10/16 by Monika Singh · 128 citations
Computer Science · #Artificial intelligence #Biclustering #Canopy clustering algorithm #Cluster analysis #Collaborative filtering #Computer science #Data mining #Database #Fuzzy clustering #Image Retrieval and Classification Techniques #Information retrieval #Machine learning #Matrix decomposition #Recommender Systems and Techniques #Recommender system #Scalability #Strengths and weaknesses #Text and Document Classification Technologies

paper · doi:10.1007/s10115-018-1254-2

published in Knowledge and Information Systems 62(1), 1-43 (Springer Science+Business Media)

crossref issued 2018/10/16 · crossref published 2018/10/16 · crossref published-online 2018/10/16 · openalex publication_date 2018/10/16 · crossref created 2018/10/16 · crossref published-print 2020/01/01 · crossref deposited 2022/09/04 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/31 · crossref indexed 2026/08/05

Citations

• Recommender system application developments: A survey
• Matrix Factorization Techniques for Recommender Systems
• Empirical Analysis of Predictive Algorithms for Collaborative Filtering
• Proceedings of the Fourteenth Conference on Uncertainty in Artificial Intelligence (1998)
• OPTICS
• Toward the next generation of recommender systems: a survey of the state-of-the-art and possible extensions

Cited by

• JEPA4Rec: Learning Effective Language Representations for Sequential Recommendation via Joint Embedding Predictive Architecture