Classical Information Retrieval
Inverted indexes, TF-IDF and BM25, query processing, and the lexical baselines that refuse to be beaten.
4concepts
60flashcards
29minutes of reading
- 01 Dynamic Pruning with WAND and Block-Max Retrieving the exact top-k without scoring most of the candidates, by maintaining an upper bound on what each document could score and skipping everything that cannot beat the current threshold.
- 02 Learned Sparse Retrieval Using a language model to assign weights over the vocabulary, including terms not present in the text, so semantic matching runs on an inverted index instead of a vector index.