Ah, although, TF-IDF is still good to know. Semantic search hasn't eliminated the need for classical retrieval techniques. It can also be used to select a subset of words to use to create an average of word vectors for a document signature, a quick and dirty method for document embeddings.
Bag of word co-occurrences in matrix format is also a nice to know, factorizing such matrices were the original vector space model for distributional semantics and provide historical context for GloVe and the like.