Remove stop words in the given corpus.

1. Define a Stop Word List: Create a collection containing common stop words. This could be a static list within the class or loaded from an external resource.

2. Filter Stop Words in Document Processing: When calculating term frequencies (tf) and document frequencies (docFreq), exclude terms that are in the stop word list.

3. Filter Stop Words in Query Processing: When processing the search query, exclude terms from the query that are in the stop word list before calculating BM25 scores.

"Stemming maps different forms of the same word to a common "stem" - for example, the English stemmer maps connection, connections, connective, connected, and connecting to connect. So a searching for connected would also find documents which only have the other forms.

This stem form is often a word itself, but this is not always the case as this is not a requirement for text search systems, which are the intended field of use. We also aim to conflate words with the same meaning, rather than all words with a common linguistic root (so awe and awful don't have the same stem), and over-stemming is more problematic than under-stemming so we tend not to stem in cases that are hard to resolve. If you want to always reduce words to a root form and/or get a root form which is itself a word then Snowball's stemming algorithms likely aren't the right answer."

https://snowballstem.org/

English details @ https://snowballstem.org/algorithms/english/stemmer.html