In which scenario should you use key phrase extraction?
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A. B. C. D.C
Key phrase extraction is a natural language processing technique that involves identifying and extracting the most important and relevant words and phrases from a text document. The extracted key phrases provide a summary of the content and can be used for various purposes, such as indexing, search, and analysis.
Out of the given scenarios, the most suitable one for using key phrase extraction is option C - identifying which documents provide information about the same topics. This is because key phrase extraction can be used to extract the most important terms from each document and compare them to identify documents that contain similar topics. This technique can be used in many applications, such as document clustering, topic modeling, and information retrieval.
Option A, identifying whether reviews of a restaurant are positive or negative, is better suited for sentiment analysis, which involves determining the emotional tone of a piece of text. In this scenario, the key phrases may not provide much insight into the sentiment of the reviews.
Option B, generating captions for a video based on the audio track, would require speech-to-text transcription and caption generation techniques, rather than key phrase extraction.
Option D, translating a set of documents from English to German, would require machine translation techniques, which involve converting the entire text of the documents from one language to another, rather than extracting key phrases.
In summary, key phrase extraction is a useful technique for identifying documents that contain similar topics, and it may not be the best fit for other scenarios such as sentiment analysis, caption generation, or machine translation.