5 real-world applications of natural language processing (NLP)
Natural language processing (NLP) is a field of study that focuses on enabling computers to understand and interpret human language. NLP involves applying machine learning algorithms to analyze and process natural language data, such as text or speech.
NLP has recently been incorporated into a number of practical applications, including sentiment analysis, chatbots and speech recognition. NLP is being used by businesses in a wide range of sectors to automate customer care systems, increase marketing initiatives and improve product offers.
Related: 5 natural language processing (NLP) libraries to use
Specifically, this article looks at sentiment analysis, chatbots, machine translation, text summarization and speech recognition as five instances of NLP in use in the real world. These applications have the potential to revolutionize the way one communicates with technology, making it more natural, intuitive and user-friendly.
NLP can be used to analyze text data to determine the sentiment of the writer toward a particular product, service or brand. This is used in applications such as social media monitoring, customer feedback analysis and market research.
A common use of NLP is sentiment analysis of the stock market, in which investors and traders examine social media sentiment on a particular stock or market. An investor, for instance, can use NLP to examine tweets or news stories about a specific stock to ascertain the general attitude of the market toward that stock. Investors can determine whether these sources are expressing positive or negative opinions about the stock by studying the terminology used in these sources.
By supplying information on market sentiment and enabling investors to modify their strategies as
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