Separating core and noncore knowledge: An application of neural network rule extraction to a cross-national study of brand image perception

• Main Authors: Setiono, Rudy, Pan, Shan L., Hsieh, Ming Huei, Azcarraga, Arnulfo P.
• Format: text
• Published: Animo Repository 2005
• Subjects: Brand choice; Consumers' preferences; Neural networks (Computer science); Sentiment analysis; Computer Sciences
• Online Access: https://animorepository.dlsu.edu.ph/faculty_research/2374; https://animorepository.dlsu.edu.ph/context/faculty_research/article/3373/type/native/viewcontent
• Institution: De La Salle University

Recent advances in algorithms that extract rules from artificial neural networks make it feasible to use neural networks as a tool for acquiring knowledge hidden in the data. Findings are reported from the use of such algorithms to separate core and noncore knowledge in a cross-national study of aut...