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Quiz Topic - Natural Language Processing
1.
Natural Language processing is used in-
A. Text classification
B. Topic modeling
C. Chatbots
D. All of the above
view answer:
D. All of the above
2.
Which of the follwing is an appication of NLP?
A. Summarizing a text or article
B. Predicting the genre of books
C. Speech recognition
D. All of the above
view answer:
D. All of the above
3.
Which of the following library is used in NLP?
A. NLTK
B. sklearn
C. pandas
D. All of the above
view answer:
D. All of the above
4.
What is tokenization?
A. Breaking sentences into words
B. Creating a set of vocabularies
C. Removing stopwords
D. All of the above
view answer:
D. All of the above
5.
Why we use named entity recognition in NLP?
A. Classify entities into predefined labels
B. Creating a set of vocabularies
C. Breaking sentences into words
D. None
view answer:
A. Classify entities into predefined labels
6.
What is machine translation?
A. Converting a human language to another
B. Converting a human language to machine language
C. Converting any human language to English
D. None
view answer:
B. Converting a human language to machine language
7.
Google translator is an application of-
A. Sentiment analysis
B. Information extraction
C. Information retrieval
D. Machine translation
view answer:
D. Machine translation
8.
Which of the following is the main challenge of NLP?
A. Handling ambiguity of documents
B. Handling POS tagging
C. Handling tokenization
D. All of the above
view answer:
D. All of the above
9.
A bag of words model uses-
A. A vocabulary of known words
B. A measure of the presence of known words
C. Both A and B
D. None
view answer:
C. Both A and B
10.
Which of these techniques is used for normalization in text mining?
A. Stemming
B. Stop words removal
C. Lemmatization
D. All of the above
view answer:
D. All of the above
11.
What stemming refers to in text mining?
A. Reducing a word to its root
B. Defining the parts of speech of a word
C. Converting sentences to words
D. None
view answer:
A. Reducing a word to its root
12.
Which is the correct order for preprocessing in Natural Language Processing?
A. tokenization->stemming->lemmatization
B. lemmatization->tokenization->stemming
C. stemming->tokenization->lemmatization
D. None
view answer:
A. tokenization->stemming->lemmatization
13.
Bag of Words in text preprocessing is a-
A. Feature scaling technique
B. Feature extraction technique
C. Feature selection technique
D. None
view answer:
B. Feature extraction technique
14.
In text mining, how the words ‘lovely’ is converted to ‘love’-
A. By stemming
B. By tokenization
C. By lemmatization
D. None
view answer:
A. By stemming
15.
Stop words are-
A. words that frequently found in a document
B. words that have no use in prediction
C. words that are not important for text mining
D. All of the above
view answer:
D. All of the above
16.
Which of the following algorithms is widely used for text classification?
A. Decision tree
B. Support vector machine
C. Naive Bayes
D. All of the above
view answer:
D. All of the above
17.
From the sentence “Ai Online Course”, how many bigrams can be created?
A. 2
B. 3
C. 4
D. 5
view answer:
A. 2
18.
Sentiment analysis is an area of:
A. Computer vision
B. Natural language processing
C. Data analysis
D. Data mining
view answer:
B. Natural language processing
19.
Which of the following is true about Topic Modelling?
A. It’s a natural language processing task
B. It is unsupervised learning
C. LDA(latent Dirichlet allocation) can be used
D. All of the above
view answer:
D. All of the above
20.
Which of the following is used to reduce the dimensionality of text data?
A. Keyword Normalization
B. Latent Dirichlet Allocation
C. Latent Semantic Indexing
D. All of the above
view answer:
D. All of the above
21.
What is the role of NLP in recommendation engines like Collaborative Filtering?
A. Extracting features from text
B. Measuring semantic similarity
C. Constructing feature vector
D. All of the above
view answer:
D. All of the above
22.
Which of the following is the feature of a text corpus?
A. Count of the word
B. Part of speech tag
C. Both A and B
D. None
view answer:
C. Both A and B
23.
Word2vec is used to-
A. Generate vectors out of words
B. Represent a document numerically
C. Make a set of vocabularies
D. None
view answer:
A. Generate vectors out of words
24.
tf - idf is used in-
A. Sentiment analysis
B. Topic modeling
C. Text summarization
D. All of the above
view answer:
D. All of the above
25.
Which of the following algorithm is not used in NLP?
A. Naive Bayes
B. BERT
C. Convolutional Neural Networks
D. None
view answer:
D. None
26.
Convolutional Neural Network is used in-
A. Image classification
B. Text classification
C. Computer vision
D. All of the above
view answer:
D. All of the above
27.
tf - idf represents-
A. How important a word is to a document in a collection or corpus
B. Where to find a word in a document
C. The length of a document
D. All of the above
view answer:
D. All of the above
28.
tf - idf is used in-
A. Page ranking by search engines
B. Processing texts for ML models
C. Both A and B
D. None
view answer:
C. Both A and B
29.
Sentiment analysis is used to-
A. detect polarity of a text
B. detect the impact of a text
C. Both A and B
D. None
view answer:
D. None
30.
Which of the following is a kind of text summarization?
A. Topic-based summarization
B. Extraction-based summarization
C. History-based summarization
D. All of the above
view answer:
B. Extraction-based summarization
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