A financial compliance team needs to extract company names, executive names, and monetary amounts from financial reports to detect potential insider trading. The reports contain both structured tables and unstructured narrative text. Which combination of techniques should they use?

Use topic modeling to identify sections about insider trading

Use sentiment analysis to identify positive or negative mentions of companies

Use only NER on the entire document, including tables

Use NER to extract entities from the narrative text and a separate parser for structured tables

What is the primary goal of topic modeling, such as Latent Dirichlet Allocation (LDA)?

To extract named entities such as people, organizations, and locations from text

To discover latent themes or topics that are present across a collection of documents

To determine the sentiment polarity of each document in a corpus

To classify documents into predefined categories based on labeled training data

What is the primary advantage of TF-IDF over simple word counts in a bag-of-words representation?

It converts words into dense vector representations that capture semantic similarity

It automatically removes all stop words from the vocabulary

It reduces the importance of words that appear frequently across many documents

It preserves the order of words in the original text

Which of the following is an example of a named entity?

The word 'running' in a sports article

The adjective 'beautiful' in a product review

The conjunction 'and' in a sentence

In Latent Dirichlet Allocation (LDA), what does each document in the corpus consist of?

A single topic that is assigned to the entire document

A sequence of words that are ordered by their importance to the document

A mixture of topics, with each word generated from one of those topics

A fixed number of words that are all drawn from the same topic

Dell Data Science Foundations

Domain 4Objective 8

Text Analytics DATA-SCIENCE-FOUNDATIONS Practice Questions (Page 1)

Part of the Advanced Analytics - Theory, Application, and Interpretation of Results for Eight Methods domain, which accounts for 40% of the DATA-SCIENCE-FOUNDATIONS exam.

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Questions 1–5

1expert · hard
A financial compliance team needs to extract company names, executive names, and monetary amounts from financial reports to detect potential insider trading. The reports contain both structured tables and unstructured narrative text. Which combination of techniques should they use?
Select an answer first
2foundation · easy
What is the primary goal of topic modeling, such as Latent Dirichlet Allocation (LDA)?
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3foundation · easy
What is the primary advantage of TF-IDF over simple word counts in a bag-of-words representation?
Select an answer first
4foundation · easy
Which of the following is an example of a named entity?
Select an answer first
5foundation · easy
In Latent Dirichlet Allocation (LDA), what does each document in the corpus consist of?
Select an answer first

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