Q.16 Which one of the following are keyword Normalization techniques in NLP1. Part of Speech2. Named entity recognition3. Stemming4. Count Vectorizer

The keyword normalization techniques in Natural Language Processing (NLP) from the given options are:

1. Part of Speech: This is not a keyword normalization technique. It is a grammatical term that deals with the roles of words when they are used in context.

2. Named Entity Recognition: This is not a keyword normalization technique either. Named Entity Recognition (NER) is a process where an algorithm takes a string of text (sentence or paragraph) as input and identifies relevant nouns (people, places, and organizations) that are mentioned in that string.

3. Stemming: This is a keyword normalization technique. Stemming is the process of reducing inflected (or sometimes derived) words to their word stem, base or root form.

4. Count Vectorizer: This is not a keyword normalization technique. Count Vectorizer is used to transform a given text into a vector on the basis of the frequency (count) of each word that occurs in the entire text.

So, out of the given options, only Stemming is a keyword normalization technique in NLP.