Machine Learning

Machine learning is a sub-field of computer science that advanced from pattern recognition and computational learning theory in AI. Machine learning study and develop calculations or algorithms that can gain from and make prediction on data. In machine learning, there are many algorithms used such as classification, clustering, regression, feature selection, and collaborative filtering/ recommendation systems etc. Many database and decision support systems are developed using these techniques for example finance, retail, and E-commerce. The recommendation system of Amazon.com is a fine example of machine learning because it can identify how the customer behave in buying therefore it give more opportunity for customers to search as similar recommended product will appear. Besides, Amazon developed its own algorithm called item-to-item collaborative filtering. The main function of this algorithm is instead of discovering neighborhood users who have the same interest on items, it finds the items acquired to be purchased together with the selected item. Among these items, customer can find item similarity because Amazon has statistics on what percentage of people will buy. (174 words)

Written by Sim Zheng Chi

Reference:

Greg Linden, B. S. a. J. Y., 2013. Amazon.com Recommendations Item-to-Item Collaborative Filtering, s.l.: IEEE INTERNET COMPUTING.