# Is it possible to calculate precision/recall for a bag-of-words model?

Suppose I have a list of keywords given to a document:

{keyword, extract, graph, represent, text, weight, number, document}


and then I have the keywords generated by a model:

{extract, keyword, weight, analysis, representation, search}


Is it possible to extimate precision/recall and F1 score for this kind of data?

Would I do it for every document if I work with a corpus and then take a mean to evaluate how well the model works?