Text Preprocessing QUIZ (MCQ QUESTIONS AND ANSWERS)

Total Correct: 0

Time:20:00

Question: 1

Why is lowercasing a common step in text preprocessing?

To enhance data quality

To improve model performance

To ensure uniformity

To handle rare words

Question: 2

What is the term for the process of reducing a word to its base form by removing suffixes?

Tokenization

Stopword removal

Lemmatization

Stemming

Question: 3

Which text preprocessing step is most critical for ensuring privacy in redacting sensitive information like names or addresses?

Tokenization

Stopword removal

Anonymization

Lemmatization

Question: 4

Which text preprocessing technique is used to handle text data in different languages?

Tokenization

Multilingual lemmatization

Stopword removal

Vectorization

Question: 5

In text preprocessing, what is the purpose of feature engineering?

Converting text to lowercase

Creating new features from existing text data

Removing special characters

Removing rare words

Question: 6

What is the term for the process of breaking a text into sentences or smaller segments?

Tokenization

Stopword removal

Sentence segmentation

Lemmatization

Question: 7

Which text preprocessing step can help identify and handle negations like "not good" in sentiment analysis?

Tokenization

Stopword removal

Lemmatization

Phrase splitting

Question: 8

What is the primary goal of text preprocessing in sentiment analysis?

Removing all positive words

Converting text to binary code

Preparing text data for sentiment classification

Removing all punctuation marks

Question: 9

Which text preprocessing technique is used to remove URLs and email addresses from text data?

Tokenization

Regular expressions

Stopword removal

Lemmatization

Question: 10

In text preprocessing, what is the purpose of TF-IDF?

Tokenization of text

Removing stopwords

Weighting the importance of terms in a document

Identifying rare words

Question: 11

Which text preprocessing step is most likely to improve search engine query performance?

Tokenization

Stopword removal

Stemming

Lemmatization

Question: 12

What is the purpose of n-grams in text preprocessing?

Reducing text dimensionality

Capturing word order and context in text

Removing punctuation marks

Converting text to lowercase

Question: 13

Which text preprocessing technique helps in reducing the impact of very common words in text analysis?

Lowercasing

Stopword removal

Tokenization

Lemmatization

Question: 14

What is the purpose of one-hot encoding in text preprocessing?

Reducing the dimensionality of text data

Converting text data into binary vectors

Removing stopwords from text

Tokenizing text data

Question: 15

Which text preprocessing technique helps in handling variations of a word, such as "running" and "run"?

Lemmatization

Tokenization

Stemming

Stopword removal

Question: 16

What is the primary purpose of text preprocessing in natural language processing (NLP)?

To remove all punctuation marks

To prepare text data for analysis and modeling

To tokenize words into individual letters

To convert text into binary code

Question: 17

In text preprocessing, what is the purpose of padding in the context of sequence data?

Adding spaces at the beginning and end of a sentence

Making all sequences the same length by adding filler tokens

Removing unnecessary spaces from text

Adjusting the text's alignment

Question: 18

Which text preprocessing step is essential for converting text data into numerical features for machine learning models?

Lemmatization

Stopword removal

Tokenization

Vectorization

Question: 19

What does the term "Bag of Words" refer to in text preprocessing?

A way to store words in a physical bag

A model that captures word order in text

A technique for representing text data as a collection of words, ignoring word order

A method for tokenizing text data

Question: 20

Which of the following is an example of a text normalization technique in text preprocessing?

Removing numbers

Converting abbreviations to full words

Removing punctuation marks

Removing whitespace

Question: 21

What is the main purpose of removing stopwords in text preprocessing?

To speed up text processing

To eliminate uncommon words

To focus on content-carrying words

To increase the document's length

Question: 22

Which of the following is not a common use case for text preprocessing?

Sentiment analysis

Document classification

Image recognition

Text summarization

Question: 23

What is the purpose of stemming in text preprocessing?

Identifying proper nouns

Removing irrelevant words

Reducing words to their root form

Removing special characters

Question: 24

Which text preprocessing technique helps convert all text to a consistent case, usually lowercase?

Tokenization

Stopword removal

Lemmatization

Lowercasing

Question: 25

Which of the following is not a common method for handling missing data in text preprocessing?

Removing the entire document

Replacing with a placeholder like "UNKNOWN"

Filling in missing values with a predefined word

Ignoring missing data

Question: 26

Which technique removes HTML tags and special characters from text data?

Stemming

Lemmatization

Regular expressions

Tokenization

Question: 27

What are stopwords in text preprocessing?

Important keywords

Common words that are typically removed from text

Proper nouns

Words with special characters

Question: 28

Which text preprocessing technique reduces words to their base or root form?

Lowercasing

Stopword removal

Lemmatization

Tokenization

Question: 29

What is tokenization in text preprocessing?

Converting text to lowercase

Removing punctuation marks

Splitting text into individual words or tokens

Converting text to binary code

Question: 30

Which of the following is not a common text preprocessing step?

Stemming

Lemmatization

Removing stopwords

Capitalization

Text Preprocessing QUIZ (MCQ QUESTIONS AND ANSWERS)

TIME:20:00

Time:20:00

Why is lowercasing a common step in text preprocessing?

What is the term for the process of reducing a word to its base form by removing suffixes?

Which text preprocessing step is most critical for ensuring privacy in redacting sensitive information like names or addresses?

Which text preprocessing technique is used to handle text data in different languages?

In text preprocessing, what is the purpose of feature engineering?

What is the term for the process of breaking a text into sentences or smaller segments?

Which text preprocessing step can help identify and handle negations like "not good" in sentiment analysis?

What is the primary goal of text preprocessing in sentiment analysis?

Which text preprocessing technique is used to remove URLs and email addresses from text data?

In text preprocessing, what is the purpose of TF-IDF?

Which text preprocessing step is most likely to improve search engine query performance?

What is the purpose of n-grams in text preprocessing?

Which text preprocessing technique helps in reducing the impact of very common words in text analysis?

What is the purpose of one-hot encoding in text preprocessing?

Which text preprocessing technique helps in handling variations of a word, such as "running" and "run"?

What is the primary purpose of text preprocessing in natural language processing (NLP)?

In text preprocessing, what is the purpose of padding in the context of sequence data?

Which text preprocessing step is essential for converting text data into numerical features for machine learning models?

What does the term "Bag of Words" refer to in text preprocessing?

Which of the following is an example of a text normalization technique in text preprocessing?

What is the main purpose of removing stopwords in text preprocessing?

Which of the following is not a common use case for text preprocessing?

What is the purpose of stemming in text preprocessing?

Which text preprocessing technique helps convert all text to a consistent case, usually lowercase?

Which of the following is not a common method for handling missing data in text preprocessing?

Which technique removes HTML tags and special characters from text data?

What are stopwords in text preprocessing?

Which text preprocessing technique reduces words to their base or root form?

What is tokenization in text preprocessing?

Which of the following is not a common text preprocessing step?