DMC Text Mining & Natural Language Processing 3

Question 1

Which algorithm is commonly used to build a text classifier based on Bayes' theorem and the assumption of feature independence?

Accepted Answer

Naive Bayes

Answer

Naive Bayes applies Bayes' theorem with the 'naive' assumption that features (words) are conditionally independent, making it efficient for text classification.

Question 2

What does the term 'n-gram' refer to in text mining?

Accepted Answer

A contiguous sequence of n items (words or characters) from a text

Answer

An n-gram is a contiguous sequence of n items from text; bigrams (n=2) and trigrams (n=3) capture local word context better than single words.

Question 3

Latent Semantic Analysis (LSA) in text mining primarily uses which mathematical technique?

Accepted Answer

Singular Value Decomposition (SVD)

Answer

LSA applies SVD to the term-document matrix to reduce dimensionality and reveal latent semantic relationships between terms and documents.

Question 4

In topic modeling, what does a 'document-topic distribution' represent?

Accepted Answer

The proportion of each topic present in a given document

Answer

In topic models like LDA, each document is represented as a probability distribution over topics, showing how much each topic contributes to the document.

Question 5

Which text preprocessing step involves converting all characters to a uniform case?

Accepted Answer

Case normalization

Answer

Case normalization (typically lowercasing) ensures that 'Apple', 'apple', and 'APPLE' are treated as the same token during analysis.

DMC - Data Mining Certification Practice Test

DMC - Data Mining Certification Practice Test

DMC Text Mining & Natural Language Processing 3