An Improved Fusion-Based Semantic Similarity Measure for Effective Collaborative Filtering Recommendations

An Improved Fusion-Based Semantic Similarity Measure for Effective Collaborative Filtering Recommendations

Abstract Semantic-enhanced recommendation systems are promising approaches to overcome the sparsity and cold-start problems, which are hard to handle using the conventional collaborative filtering (CF) approaches. Further research is needed to effectively integrate ontologies into collaborative filt...

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Bibliographic Details
Main Authors: Malak Al-Hassan, Bilal Abu-Salih, Esra’a Alshdaifat, Ahmad Aloqaily, Ali Rodan
Format: Article
Language:English
Published: Springer 2024-03-01
Series:International Journal of Computational Intelligence Systems
Subjects:
Semantic similarity
Ontology
Recommender system
Collaborative filtering
Personalization services
Online Access:https://doi.org/10.1007/s44196-024-00429-4

Internet

https://doi.org/10.1007/s44196-024-00429-4

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