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CFA Level I · CFA Level I Exam · Introduction to Financial Data Science

A data scientist wants to reduce the words "earned", "earning" and "earnings" to a common base form, using a rule-based procedure that strips suffixes and may produce a non-dictionary token such as "earn" or "earnin". Compared with lemmatization, this procedure is most likely:

The procedure described is stemming, which is less computationally costly but less accurate than lemmatization. It strips suffixes by rule and can output non-dictionary tokens. Lemmatization uses morphological analysis to return valid base words, so it is more accurate but more expensive.

  1. Amore computationally costly and always returns valid dictionary words
  2. Bless computationally costly and less accurateCorrect
  3. Cequivalent in output because both use morphological analysis of each word

Explanation

The described procedure is stemming. It applies simple suffix-stripping rules, so it is cheaper than lemmatization but can yield non-words and be less accurate. Lemmatization uses morphological analysis to return valid base forms and costs more.

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