A Developed Collaborative Filtering Similarity Method to Improve the Accuracy of Recommendations under Data Sparsity

• Main Authors: Al-Bashiri, Hael, Abdulgabber, Mansoor Abdullateef, Awanis, Romli, Norazuwa, Salehudin
• Format: Article
• Language: English
• Published: The Science and Information (SAI) Organization Limited 2018
• Subjects: QA75 Electronic computers. Computer science
• Online Access: http://umpir.ump.edu.my/id/eprint/21368/1/A%20Developed%20Collaborative%20Filtering%20Similarity-fskkp-2018.pdf; http://umpir.ump.edu.my/id/eprint/21368/; http://dx.doi.org/10.14569/IJACSA.2018.090423
• Institution: Universiti Malaysia Pahang

This paper presented a new similarity method to improve the accuracy of traditional Collaborative Filtering (CF) method under sparse data issue. CF provides the user with items, that what they need, based on analyses the preferences of users who have a strong correlation to him/her preference. Howev...