Artificial Intelligence MCQ Questions - Text Mining

Text Mining MCQs : This section focuses on "Text Mining" in Artificial Intelligence. These Multiple Choice Questions (MCQ) should be practiced to improve the AI skills required for various interviews (campus interviews, walk-in interviews, company interviews), placements, entrance exams and other competitive examinations.

1. ___________ is the process of transforming unstructured text into a structured format to identify meaningful patterns and new insights.

A. Data mining
B. Text mining
C. File mining
D. Deep mining

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2. In which database, data is a blend between structured and unstructured data formats?

A. Full-structured data
B. Partial-structured data
C. Semi-structured data
D. Uni-structured data

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3. The process of breaking out long-form text into sentences and words called?

A. Stem
B. Cluster
C. Bag
D. Tokens

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4. Text mining is being used by large media companies, to clarify information and to provide readers with greater search experiences,

A. TRUE
B. FALSE
C. Can be true or false
D. Can not say

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5. Typical text mining tasks include?

A. text categorization
B. text clustering
C. entity relation modeling
D. All of the above

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6. Which of the following technique is not a part of flexible text matching?

A. Soundex
B. Metaphone
C. Keyword Hashing
D. Edit Distance

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7. What is the right order for a text classification model components?

A. Text cleaning -> Text annotation -> Gradient descent -> Model tuning -> Text to predictors
B. Text cleaning -> Text annotation -> Text to predictors -> Gradient descent -> Model tuning
C. Text cleaning -> Gradient descent -> Model tuning -> Text to predictors -> Text annotation
D. Text cleaning -> Text annotation -> Model tuning -> Text to predictors -> Gradient descent

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8. What are the possible features of a text corpus?

A. Count of word in a document
B. Vector notation of word
C. Part of Speech Tag
D. All of the above

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9. What is the major difference between CRF (Conditional Random Field) and HMM (Hidden Markov Model)?

A. CRF is Generative whereas HMM is Discriminative model
B. Both CRF and HMM are Generative model
C. CRF is Generative whereas HMM is Discriminative model
D. Both CRF and HMM are Discriminative mode

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10. Stemming: This refers to the process of separating the prefixes and suffixes from words to derive the root word form and meaning.

A. TRUE
B. FALSE
C. Can be true or false
D. Can not say

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