Examples of Natural Language Processing in Everyday Life

In addition, there is also the risk of misinterpreting the data . It could be due to fatigue or judgments that are too subjective. Fortunately, this can be overcome with nlp technology. Because, nlp-supported tools can analyze the data as it is. The machine also won’t give a biased assessment, so the results of the analysis can be more accurate. 2. Examining lots of data at once still with the same scenario as the example above. If you are researching hundreds of data at the same time, of course this will be very tiring. Meanwhile, nlp is capable of analyzing large amounts of text data. Starting from consumer reviews, comments on social media accounts, and so on. 3. Reducing analysis costs if you want to recruit people to do data analysis manually, of course you have to prepare a salary budget first. It is not certain that the results will be obtained in the near future, because the analysis must be done one by one, and humans have limitations in the form of working hours.

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It’s different with nlp-supported text analysis tools, you can use them 24 hours non-stop. The results of the analysis can also be obtained in a much shorter time. 4. Understand the market better can you understand the market without nlp? Certainly can. But, nlp offers an easier way. You can find out market sentiment instantly using nlp. For example, you can research hundreds of consumer reviews online to find out whether consumers’ views of your product are positive or vice versa. That way, you will know what you have to do to satisfy market desires. Illustration of handshake after interview 5. Increase customer satisfaction Ukraine WhatsApp Number List you can also use nlp to serve customers, you know. For example, suppose your business offers support services with a ticket system. Now, from the various tickets that have been received, nlp can sort complaints and questions based on their topic and urgency.

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So, you can easily find out which tickets have the highest level of urgency, and also group tickets whose contents are more or less similar. Very practical, right? Also read: programming data types that programmers must know how does nlp work? After knowing the various benefits above, surely you are curious about how natural language processing works? Since nlp is a branch of artificial intelligence , the way it works can be considered semi-automatic. In the beginning, you have to “teach” the machine how to “read” correctly, then the Mobile Lead machines will try to understand the words they find on their own. Illustration of typing on a keyboard on a laptop at least that’s the easy explanation. However, if you want to explain in more detail, the flow of how nlp works is more or less like this: nlp will do text vectorization first .

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