Employing singular value decomposition and similarity criteria for alleviating cold start and sparse data in context-aware recommender systems
KV Rodpysh, SJ Mirabedini, T Banirostam - Electronic Commerce …, 2023 - Springer
The recommender system's primary purpose is to estimate the user's desire and provide a
list of items predicted from the appropriate information. Also, context-aware recommendation …
list of items predicted from the appropriate information. Also, context-aware recommendation …
A comparative analysis of computational drug repurposing approaches: proposing a novel tensor-matrix-tensor factorization method
Efficient drug discovery relies on drug repurposing, an important and open research field.
This work presents a novel factorization method and a practical comparison of different …
This work presents a novel factorization method and a practical comparison of different …
[HTML][HTML] Hybrid Method of Recommender System to Decrement Cold Start and Sparse Data Issues
K Vahidy Rodpysh, SJ Mirabedini… - Journal of Electrical …, 2020 - journals.sru.ac.ir
Background and Objectives: The main purpose of the recommender system is to estimate
the user's desire and provide a list of items predicted using the appropriate information …
the user's desire and provide a list of items predicted using the appropriate information …
[PDF][PDF] HOSPITALITY REFERRAL SYSTEMS WITH INTELLIGENT COLLABORATIVE DATA ANALYTICS FILTERING BASED ON MACHINE LEARNING
EM POTE, S SHUKLA - researchgate.net
Throughout numerous commercial areas, researchers and operators have stressed the
importance of great consumer interactions and eventual word-of-mouth. In a consequence …
importance of great consumer interactions and eventual word-of-mouth. In a consequence …