Stemmers vs Lemmatizers
Natural Language Processing (NLP), especially for English, has evolved into the stage where stemming would become an archaic technology if "perfect" lemmatizers exist. It's because stemmers change the surface form of a word/token into some meaningless stems. Then again the definition of the "perfect" lemmatizer is questionable because different NLP task would have required different level of lemmatization. E.g. Convert words between verb/noun/adjective forms . Stemmers [in]: having [out]: hav Lemmatizers [in]: having [out]: have So the question is, are English stemmers any useful at all today?