Recommendation system depend on user rating and favorite list
You can use collaborative filtering. From the user ratings you can define a ratings matrix with missing ratings that your algorithm will predict to recommend items to users. 

The items data and user's whishlist can be included as auxiliary information (basically you cluster Sakes given their alcohol percentage, polish percentage and acidity and users given their whishlist using a K-mean algorithm). Have a look at this paper:

https://pdfs.semanticscholar.org/a0bc/3d1c05da5b57bee066368ffd0839247832c8.pdf