A research team is analyzing 1,000 academic papers to find the most distinctive terms for each paper. They notice that the word 'study' appears in 90% of papers, while 'quantum' appears in only 2%. They want to rank terms so that 'quantum' is considered more important for the papers that contain it. Which technique should they use?

TF-IDF with a high inverse document frequency weight for rare terms

Word embeddings similarity to 'research'

Which of the following is a core challenge that NLP systems must address?

The need to manually label every word in a sentence before processing

Ambiguity in language, where the same word or phrase can have multiple meanings depending on context

The requirement to use only English language data

The inability to store text data in binary format

Which statement best describes how topic modeling treats documents?

Each document is ignored if it contains stop words

Each document is considered a mixture of multiple topics

Each document is assigned to exactly one topic

Each document is treated as a single vector of word counts

A data scientist is building a system to automatically tag support tickets with the most relevant product area. The corpus contains 50,000 historical tickets, and each ticket averages 200 words. The team wants to weight words by how distinctive they are to a particular ticket, rather than just how frequent they are. Which technique should the data scientist use?

Byte-pair encoding tokenization

CompTIADataX

Domain 5Objective 2

NLP Concepts DY0-001 Practice Questions (Page 1)

Part of the Specialized applications of data science domain, which accounts for 13% of the DY0-001 exam. CompTIA does not publish an official question count, but from its 165-minute exam (~65–110 total, ~8–14 in this domain), expect 2–4 from this objective — we provide 31 practice questions to prepare you well beyond it. (estimate)

31questions here

7free pages

6concepts

13%of the exam

Questions 1–5

1application · medium
A research team is analyzing 1,000 academic papers to find the most distinctive terms for each paper. They notice that the word 'study' appears in 90% of papers, while 'quantum' appears in only 2%. They want to rank terms so that 'quantum' is considered more important for the papers that contain it. Which technique should they use?
Select an answer first
2foundation · easy
Which of the following is a core challenge that NLP systems must address?
Select an answer first
3foundation · easy
Which statement best describes how topic modeling treats documents?
Select an answer first
4foundation · easy
Which NLP application is primarily used to determine the emotional tone expressed in a piece of text?
Select an answer first
5application · medium
A data scientist is building a system to automatically tag support tickets with the most relevant product area. The corpus contains 50,000 historical tickets, and each ticket averages 200 words. The team wants to weight words by how distinctive they are to a particular ticket, rather than just how frequent they are. Which technique should the data scientist use?
Select an answer first

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NLP Concepts DY0-001 Practice Questions (Page 1)

Questions 1–5

Which of the following is a core challenge that NLP systems must address?

Which statement best describes how topic modeling treats documents?

Which NLP application is primarily used to determine the emotional tone expressed in a piece of text?

Keep studying — Specialized applications of data science