Classical Information Retrieval
Inverted indexes, TF-IDF and BM25, query processing, and the lexical baselines that refuse to be beaten.
7concepts
141flashcards
51minutes of reading
- 01 BM25 and Term Frequency Saturation Why a term appearing twenty times should not score ten times higher than one appearing twice, how BM25 encodes that as a saturating function, and what its two parameters actually control.
- 02 Inverted Indexes and Postings Lists The data structure that makes text search sublinear in corpus size, why postings are stored as sorted document IDs, and how gap encoding turns a list of integers into a few bits each.
- 03 TF-IDF and the Vector Space Model Queries and documents as weighted term vectors ranked by cosine, why each weight multiplies local and collection-wide evidence, and why plain cosine normalisation systematically favours short documents.