Exploration of Data Mining Techniques Supporting Recommendation Systems

Recommendation systems are the most significant auxiliary feature of many online services. This project aims to explore techniques for data cleaning and feature extraction in data mining. Using these techniques we aim to identify, extract, and create features which are useful in recommendation systems. Several approaches are discussed such as Principal Component Analysis, Single-Value Decomposition, and Graph Clustering.