In a research project, Professor Smith is analyzing a large corpus of scientific articles. He wants to remove common words like "the," "is," and "a," which do not contribute much to the analytic…

The correct answer is D. Removing stop words. Stop words are high-frequency words in any language that generally carry little meaning or analytic relevance, so they are often excluded as part of text preprocessing in natural language processing (NLP). This step helps reduce noise and focuses analysis on the most…

Data Processing Technologies

Question

In a research project, Professor Smith is analyzing a large corpus of scientific articles. He wants to remove common words like “the,” “is,” and “a,” which do not contribute much to the analytic value of the text. Which text preprocessing step should Professor Smith use?

Options

ATokenization
BStemming
CLemmatization
DRemoving stop words

How the community answered

(54 responses)

A
2% (1)
B
2% (1)
C
6% (3)
D
91% (49)

Explanation

Stop words are high-frequency words in any language that generally carry little meaning or analytic relevance, so they are often excluded as part of text preprocessing in natural language processing (NLP). This step helps reduce noise and focuses analysis on the most substantive terms within scientific articles, improving both computational efficiency and the outcomes of search and statistical modeling tasks.

Topics

#NLP#stop words#text preprocessing#tokenization

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