Learn what natural language processing (NLP) is and how it is used in various applications, such as sentiment analysis, text summarization, machine translation, and question answering.
Table of Contents
Question
Monitoring public news sites for negative mentions of a product is an example of natural language processing. True or False?
A. True
B. False
Answer
A. True
Explanation
Monitoring public news sites for negative mentions of a product is an example of natural language processing.
The correct answer is A. True. Monitoring public news sites for negative mentions of a product is an example of natural language processing (NLP). NLP is a branch of artificial intelligence that deals with the interaction between computers and human languages, such as speech and text. NLP enables computers to understand, analyze, generate, and manipulate natural language data. Some of the common applications of NLP are:
- Sentiment analysis: This is the process of identifying and extracting the emotional tone and attitude of a speaker or writer towards a topic, product, or service. Sentiment analysis can help businesses monitor customer feedback, reviews, and social media posts to measure customer satisfaction, loyalty, and preferences. For example, a company can use sentiment analysis to track how customers feel about their products or services based on the positive or negative words they use in their online comments.
- Text summarization: This is the process of creating a concise and informative summary of a longer text document. Text summarization can help users quickly grasp the main points and key information of a text without reading the whole document. For example, a news aggregator can use text summarization to provide short summaries of news articles from different sources for the readers.
- Machine translation: This is the process of automatically converting text or speech from one natural language to another. Machine translation can help users communicate across language barriers and access information in different languages. For example, a traveler can use machine translation to translate signs, menus, or conversations in a foreign country.
- Question answering: This is the process of providing a direct and specific answer to a natural language question. Question answering can help users find relevant information from large and complex data sources, such as the web, databases, or documents. For example, a student can use question answering to get answers to their homework questions from the internet.
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