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Lemmatization Vs Stemming

1

$begingroup$

I have been reading about both these techniques to find the root of the word, but how do we prefer one to the other?

Is "Lemmatization" always better than "Stemming"?

nlp natural-language-process stanford-nlp

share|improve this question

asked 1 hour ago

ashirwadashirwad

63

New contributor

ashirwad is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
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add a comment | 

1

$begingroup$

I have been reading about both these techniques to find the root of the word, but how do we prefer one to the other?

Is "Lemmatization" always better than "Stemming"?

nlp natural-language-process stanford-nlp

share|improve this question

asked 1 hour ago

ashirwadashirwad

63

New contributor

ashirwad is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.

$endgroup$

add a comment | 

$begingroup$

I have been reading about both these techniques to find the root of the word, but how do we prefer one to the other?

Is "Lemmatization" always better than "Stemming"?

nlp natural-language-process stanford-nlp

share|improve this question

asked 1 hour ago

ashirwadashirwad

63

New contributor

ashirwad is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.

$endgroup$

share|improve this question

asked 1 hour ago

ashirwadashirwad

63

New contributor

ashirwad is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.

share|improve this question

asked 1 hour ago

ashirwadashirwad

63

New contributor

ashirwad is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.

asked 1 hour ago

ashirwadashirwad

63

New contributor

ashirwad is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.

asked 1 hour ago

ashirwadashirwad

63

1 Answer
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$begingroup$

I would say that lemmatization is generally the preferred way of reducing related words to a common base.

This Quora question is a good resource on the subject: Is it advisable to choose lemmatization over stemming in NLP?

The top answer quotes another good resource that motivates why lemmatization is usually better, Stemming and lemmatization, from Stanford NLP:

Stemming usually refers to a crude heuristic process that chops off
the ends of words in the hope of achieving this goal correctly most of
the time, and often includes the removal of derivational affixes.

Lemmatization usually refers to doing things properly with the use of
a vocabulary and morphological analysis of words, normally aiming to
remove inflectional endings only and to return the base or dictionary
form of a word, which is known as the lemma.

But that is just generally, it is not always better. Stemming still has some advantages and it will depend on the use case. The main reasons you would still use stemming over lemmatization would be:

• Simplicity


• Speed


• Memory constraints

share|improve this answer

edited 15 secs ago

answered 1 hour ago

Simon LarssonSimon Larsson

1,045214

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2

$begingroup$

I would say that lemmatization is generally the preferred way of reducing related words to a common base.

This Quora question is a good resource on the subject: Is it advisable to choose lemmatization over stemming in NLP?

The top answer quotes another good resource that motivates why lemmatization is usually better, Stemming and lemmatization, from Stanford NLP:

Stemming usually refers to a crude heuristic process that chops off
the ends of words in the hope of achieving this goal correctly most of
the time, and often includes the removal of derivational affixes.

Lemmatization usually refers to doing things properly with the use of
a vocabulary and morphological analysis of words, normally aiming to
remove inflectional endings only and to return the base or dictionary
form of a word, which is known as the lemma.

But that is just generally, it is not always better. Stemming still has some advantages and it will depend on the use case. The main reasons you would still use stemming over lemmatization would be:

• Simplicity


• Speed


• Memory constraints

share|improve this answer

edited 15 secs ago

answered 1 hour ago

Simon LarssonSimon Larsson

1,045214

$endgroup$

add a comment | 

2

$begingroup$

I would say that lemmatization is generally the preferred way of reducing related words to a common base.

This Quora question is a good resource on the subject: Is it advisable to choose lemmatization over stemming in NLP?

The top answer quotes another good resource that motivates why lemmatization is usually better, Stemming and lemmatization, from Stanford NLP:

Stemming usually refers to a crude heuristic process that chops off
the ends of words in the hope of achieving this goal correctly most of
the time, and often includes the removal of derivational affixes.

Lemmatization usually refers to doing things properly with the use of
a vocabulary and morphological analysis of words, normally aiming to
remove inflectional endings only and to return the base or dictionary
form of a word, which is known as the lemma.

But that is just generally, it is not always better. Stemming still has some advantages and it will depend on the use case. The main reasons you would still use stemming over lemmatization would be:

• Simplicity


• Speed


• Memory constraints

share|improve this answer

edited 15 secs ago

answered 1 hour ago

Simon LarssonSimon Larsson

1,045214

$endgroup$

add a comment | 

$begingroup$

I would say that lemmatization is generally the preferred way of reducing related words to a common base.

This Quora question is a good resource on the subject: Is it advisable to choose lemmatization over stemming in NLP?

The top answer quotes another good resource that motivates why lemmatization is usually better, Stemming and lemmatization, from Stanford NLP:

Stemming usually refers to a crude heuristic process that chops off
the ends of words in the hope of achieving this goal correctly most of
the time, and often includes the removal of derivational affixes.

Lemmatization usually refers to doing things properly with the use of
a vocabulary and morphological analysis of words, normally aiming to
remove inflectional endings only and to return the base or dictionary
form of a word, which is known as the lemma.

But that is just generally, it is not always better. Stemming still has some advantages and it will depend on the use case. The main reasons you would still use stemming over lemmatization would be:

• Simplicity


• Speed


• Memory constraints

share|improve this answer

edited 15 secs ago

answered 1 hour ago

Simon LarssonSimon Larsson

1,045214

$endgroup$

share|improve this answer

edited 15 secs ago

answered 1 hour ago

Simon LarssonSimon Larsson

1,045214

answered 1 hour ago

Simon LarssonSimon Larsson

1,045214

answered 1 hour ago

Simon LarssonSimon Larsson

1,045214