Substitute product recommendation is important to improve customer satisfaction on E-commerce domain. E-commerce in nature provides rich sources of substitute relationships, e.g., customers purchase a substitute product when the viewed product is sold out, etc. However, existing recommendation systems usually learn the product substitution correlations without jointly considering variant customer behavior
