TextSearch.jl is a package to create vector representations of text, mostly, independently of the language. It is intended to be used with SimilaritySearch.jl, but can be used independetly if needed. TextSearch.jl was renamed from TextModel.jl to reflect its capabilities and mission.

For generic text analysis you should use other packages like TextAnalysis.jl.

It supports a number of simple text preprocessing functions, and three different kinds of tokenizers, i.e., word n-grams, character q-grams, and skip-grams. It supports creating multisets of tokens, commonly named bag of words (BOW). TextSearch.jl can produce sparse vector representations based on term-weighting schemes like TF, IDF, and TFIDF. It also supports term-weighting schemes designed to cope text classification tasks, mostly based on distributional representations.

You may install the package as follows

] add TextSearch

also, you can run the set of tests as follows

] test TextSearch

The directory examples contains a few examples of how to use it, based on Pluto.jl

After cloning the repository, you must intantiate the directory.

using Pkg
pkg"instantiate"

once you instantiated your environment, just run Pluto notebook and explore the examples

using Pluto
Pluto.run()