This crate provides a library for generating and using simple text data structures that work like language models. The data structures do not use real-valued vector embeddings; instead they use the mathematical concept of multisets and are derived directly from plain text data.

The data structures are named Simple Explainable Language Multiset Representations (SELMRs) and consist of multisets created from all multi-word expressions and all multi-word-context combinations contained in a collection of documents given some contraints. The multisets can be used for downstream NLP tasks like text classifications and searching, in a similar manner as real-valued vector embeddings.

SELMRs produce explainable results without any randomness and enable explicit links with lexical, linguistical and terminological annotations. No model is trained and no dimensionality reduction is applied.

For information on how to use this package, please look here.