Refining Preference-Based Recommendation with Associative Rules and Process Mining Using Correlation Distance

Refining Preference-Based Recommendation with Associative Rules and Process Mining Using Correlation Distance

Online services, ambient services, and recommendation systems take user preferences into data processing so that the services can be tailored to the customer’s preferences. Associative rules have been used to capture combinations of frequently preferred items. However, for some item sets X and Y, on...

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Bibliographic Details
Main Authors: Mohd Anuaruddin Bin Ahmadon, Shingo Yamaguchi, Abd Kadir Mahamad, Sharifah Saon
Format: Article
Language:English
Published: MDPI AG 2023-02-01
Series:Big Data and Cognitive Computing
Subjects:
process mining
associative mining
personalization
recommendation
decision support
Online Access:https://www.mdpi.com/2504-2289/7/1/34

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https://www.mdpi.com/2504-2289/7/1/34

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