Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
384045 | Expert Systems with Applications | 2010 | 10 Pages |
Abstract
Collaborative filtering is an extensively adopted approach for commodity recommendation. This investigation presents a collaborative filtering method to support commodity recommendation of retail business according to customer preferences. Moreover, a novel recommendation methodology based on decision tree induction is also proposed to obtain further effectiveness and quality of recommendations. Effectiveness of the proposed method is evaluated by implementing a recommender system based on data mining and analyzing real retail business data to demonstrate the operability of the system.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Shao-Lun Lee,