I have data for the orders of the previous year containing the product and the seller who sold the product. I have an information product, product category, seller, delivery address price etc. Database size is more than 100,000 rows. Now, I have to suggest a seller for a totally new product based on the data I have. I tried using TF-IDF to find similar products of the same category to suggest the sellers and I got an accuracy of 70%. Then, I tried a random forest algorithm and sadly I got an accuracy of just 40%. I am unable to find a suitable approach for my use case. How can I approach this problem statement?
The Product and Seller Mapping table is like this
Product has the following information
Seller has the following information