I am supposed to train a classifier with historical shopping data that predicts the probability of an item being returned. The only human language contained for each purchase is the name of the product. Since the purchases are from many different companies all over Europe, the product names are often in different languages.
What model would be best suited to encode these product names? Would you use a translator to translate these product names? They are often riddled with abbreviations or brand names and in my eyes would most likely not lend themselves well to translations.
(I am yet to receive the data set, so I dont know exactly how many different products exist and what languages are most common, however the data set is mostly likely dominantly german and english)