You are developing a natural language processing solution in Azure. The solution will analyze customer reviews and determine how positive or negative each review is.
This is an example of which type of natural language processing workload?
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A. B. C. D.B
Sentiment Analysis is the process of determining whether a piece of writing is positive, negative or neutral.
https://docs.microsoft.com/en-us/azure/architecture/data-guide/technology-choices/natural-language-processingThe natural language processing solution described in the question is designed to analyze customer reviews and determine the positivity or negativity of each review. This is an example of a sentiment analysis workload, which is the process of using computational techniques to extract subjective information from text, such as opinions, attitudes, and emotions.
Sentiment analysis is commonly used in applications that require understanding how people feel about a product, service, or topic. For example, companies may use sentiment analysis to monitor social media activity and customer reviews to evaluate the performance of their products or services.
In Azure, sentiment analysis can be performed using several natural language processing services, such as the Text Analytics service. The Text Analytics service provides an API that developers can use to extract key phrases, detect language, and determine sentiment from text data.
To perform sentiment analysis, the Text Analytics service analyzes each sentence in the text and assigns a positive, negative, or neutral score based on the sentiment expressed in the sentence. The service then aggregates the scores for each sentence to determine an overall sentiment score for the entire text.
In conclusion, the natural language processing workload described in the question is an example of a sentiment analysis workload, which involves using computational techniques to extract subjective information from text, such as opinions, attitudes, and emotions.