Search relevance is a difficult problem in information retrieval. How do you ensure that you get the best results back from searching a collection of documents? Let's explore a few basic strategies, including simple searching, term-frequency searching, and TF-IDF searching.

• information retrieval
• nlp
• search

Term frequency-inverse document frequency is a means of assigning weight to a search term when comparing individual documents within a corpus. It is an improvement on the bag-of-words model in that it considers the relative rarity of a term within a larger corpus.

• information retrieval
• linguistics
• nlp
• reference

The bag-of-words (BoW) model is used to represent a document as a fixed-length vector of frequency counts for each token in the document. BoW models are useful in classification, machine learning, and topic modeling tasks, among others.

• information retrieval
• linguistics
• nlp
• reference