Practice Test
True/False: Key phrase extraction is the process of identifying the main topics in a text document.
- True
- False
Answer: True
Explanation: Key phrase extraction indeed performs the operation of retrieving the main topics that a body of text is talking about.
What are the typical applications of key phrase extraction?
- A. Spam filtering.
- B. Text summarization.
- C. Voice recognition.
- D. Image recognition.
Answer: B. Text summarization.
Explanation: Key phrase extraction is predominantly used in text summarization as it assists in identifying the main topics that are covered in the text.
True/False: Key phrase extraction is not useful in information retrieval.
- True
- False
Answer: False
Explanation: Key phrase extraction is quite helpful in information retrieval, as it assists in identifying and locating the most relevant information in large text datasets.
What feature of Azure Text Analytics API enables the extraction of key phrases?
- A. Syntax API
- B. Key Phrases API
- C. Sentiment Analysis API
- D. Language Detection API
Answer: B. Key Phrases API
Explanation: Azure Text Analytics offers Key Phrases API to extract key phrases from a given text document or content.
True/False: Key phrase extraction can be applied to any kind of text data.
- True
- False
Answer: True
Explanation: As far as the text data is machine-readable, key phrase extraction can be applied regardless of subject or context.
Which of the following benefits does Key Phrase Extraction provide?
- A. Helps in understanding the customer reviews.
- B. Helps websites to improve their SEO.
- C. Helps in identifying the spam mails.
- D. All of the above.
Answer: D. All of the above.
Explanation: Key Phrase Extraction is useful in all these scenarios as it helps to draw out principal topics from the text data, which aids in understanding customer feedback, improving SEO, and identifying spam emails.
True/False: Azure’s Key Phrase Extraction can only handle English language text data.
- True
- False
Answer: False
Explanation: Azure’s Key Phrase Extraction can handle multiple languages, not just English.
Key Phrase Extraction is not useful in:
- A. Legal document analysis
- B. Textual data summarization
- C. Mapping a photograph to a location
- D. Social media sentiment analysis
Answer: C. Mapping a photograph to a location
Explanation: The task of mapping a photograph to a location is more related to image analysis and geolocation, not key phrase extraction which focuses on textual data.
True/False: Key phrase extraction can’t be used in identifying the trending topics on social media.
- True
- False
Answer: False
Explanation: Key phrase extraction can indeed be used in identifying trending topics on social media by extracting the frequently occurring phrases or subject matter from posts.
What is the function of key phrase extraction in chatbots?
- A. To recognize user voice commands.
- B. To identify the main issues customer has.
- C. To map customer location.
- D. To create a graphical user interface.
Answer: B. To identify the main issues customer has.
Explanation: In chatbots, key phrase extraction is used to identify the main points or concerns that a customer is expressing, allowing for more intelligent and relevant responses.
Interview Questions
What is key phrase extraction in the context of AI and machine learning?
Key phrase extraction is the process of picking out key points, topics, and central themes from a piece of text. This task is commonly accomplished through AI and machine learning techniques, particularly involving natural language processing.
What Microsoft Azure service provides the key phrase extraction feature?
The key phrase extraction feature is provided by Azure’s Text Analytics API, which is a part of Azure Cognitive Services.
How can key phrase extraction be useful in understanding user feedback?
Key phrase extraction can help automate the process of understanding user feedback. It can identify the main points or topics that a user mentions in their feedback, aiding in the quick and efficient analysis of user sentiments.
What is Natural Language Processing in relation to key phrase extraction?
Natural Language Processing (NLP) is a subfield of AI that focuses on the interaction between computers and human language. NLP techniques are often used in key phrase extraction to help computers understand, interpret and manipulate human language in a meaningful way.
What is the prerequisite for using Text Analytics API for key phrase extraction in Azure?
To use Text Analytics API for key phrase extraction, one has to have an Azure account and should create a Text Analytics resource in the Azure portal.
How does Key Phrase Extraction work in Azure Text Analytics?
Azure Text Analytics uses advanced natural language processing techniques to extract key talking points from text. This includes noun phrases and other significant categorical phrases.
Is it possible to extract key phrases from text in different languages using the Azure Text Analytics API?
Yes, Azure Text Analytics API supports key phrase extraction in multiple languages like English, Spanish, German, Japanese, and several others.
Which programming languages support the Text Analytics API for key phrase extraction?
Languages like .NET, Python, JavaScript, and Java support the Text Analytics API for key phrase extraction.
What is “Sentiment Analysis” in Azure AI?
Sentiment analysis, also referred to as opinion mining, is a feature provided by Azure AI that uses standard natural language processing techniques to determine whether the sentiment of a piece of text is positive, negative, neutral, or mixed.
Can Key Phrase Extraction be used with large volumes of data?
Yes, Key Phrase Extraction can be used to process large volumes of data. It forms a crucial part of many big data analytics pipelines where extracting relevant information efficiently is necessary.
In what format should the text data be for it to be processed by the Text Analytics API?
The text data should be in string format. The Text Analytics API requires the data to be in this format to perform the key phrase extraction.
Can Key Phrase Extraction be used in social media analytics?
Yes, Key Phrase Extraction can be utilized in social media analytics to pull out central topics from posts, reviews, and comments to understand trends and sentiments.
How does Key Phrase Extraction help in improving SEO?
Key Phrase Extraction facilitates improved Search Engine Optimization (SEO) as it assists in understanding the prominent keywords, consequently improving content relevancy and visibility in search engine results.
What is the role of machine learning in Key Phrase Extraction?
Machine Learning is important in Key Phrase Extraction as it builds the models that learn to identify and extract important key phrases from a vast amount of textual data based on patterns and associations.
What industries typically benefit from Key Phrase Extraction?
Industries like retail, customer service, IT, marketing, and healthcare typically benefit the most from Key Phrase Extraction as it facilitates feedback analysis, trend identification, and content optimization.
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