The Porter stemming algorithm (or ‘Porter stemmer’) is a process for removing the commoner morphological and inflexional endings from words in English. It should be noted that the Porter stemming algorithm does not leave a real word after removing the stem since the main purpose of it is to bring variant forms of a word into one.


Martin Porter’s homepage
https://tartarus.org/martin/PorterStemmer/

The Porter Stemmer

Stemming a simpler but cruder alternative to the lemmatization, which mainly chops off word-final affixes. The Porter Stemmer is the most widely used stemming algorithms.

University of Michigan - Ann Arbor

Word normalization is the task of unifying words/tokens to a single standard format. The methods below are widely used depending on the tasks.

- Case folding
- Lemmatization
- Stemming

Word normalization

An on-going but a helpful book resource about NLP
https://web.stanford.edu/~jurafsky/slp3/

Speech and Language Processing (3rd ed. draft) 

Stemming

Case folding is mapping everything to lower case. Whether applying it depends on the tasks. In information retrieval or speech recognition, it is very helpful. However, for sentiment analysis and other text classification tasks, information extraction, and machine translation, keeping cases can help differentiate words. For example, US the country and us the pronoun.

Case folding

Lemmatization is the task of determining whether two words have the same root, despite their surface differences. For example, $$am$$, $$are$$, and $$is$$ have the shared lemma $$be$$; the words $$cat$$ and $$cats$$ both have the lemma $$cat$$.

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