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Natural Language Processing poses some exciting opportunities across various industries through analysis of the vast amount of data in order to deliver a better quality of service. This branch of AI considered as a critical one for navigating through the growing volume of data already in silos and generated daily. Let's explore further how NLP serves benefit in different domains.

The following are some significant use cases of NLP across different industries serving a variety of business purposes.

NLP in Neural Machine Translation

Neural machine translation has improved the imitation of professional translations over the years of its advancement. When applied in neural machine translation, natural language processing helps educate neural machine networks. This can be used by businesses to translate low impact content including emails, regulatory texts, etc. Such machine translation tools speed up communication with partners while enriching other business interactions.

NLP in Sentiment Analysis

Sentiment analysis helps in estimating customer feedback on the brand and product while adjusting sales and marketing strategy. It is also termed as opinion mining which is capable of analyzing news and blogs assigning a value to the text (negative, positive or neutral) over social media platforms. As it stands now NLP algorithms can identify emotions such as happy, annoyed, angry, sad. Through the combination of sentiment analysis and NLP, marketers will have all it takes to develop actionable strategies and make well-informed decisions.

NLP in HR and Recruiting

Using NLP in human resources, HR professionals can speed up candidate searches by filtering out relevant resumes and designing bias-proof and gender-neutral job descriptions. Also by making the use of semantic analysis, software sifts through the considerable synonyms enabling recruiters to detect candidates that meet the job requirements.

NLP in Advertising

Through the analysis of digital footprint over social media, emails, search keywords, and browsing behavior, NLP enables advertisers to identify new audiences potentially interested in their products. Even a simple keyword matching routine companies can broaden the range of channels for ad placement, helping companies spend their ad budgets more effectively and target potential clients using NLP algorithms.

NLP in Healthcare

According to Becker's Hospital Review, NLP can improve clinical documentation, data mining research, computer-assisted coding, automated registry reporting. In the context of emerging cases, it helps in clinical trial matching, clinical decision support, risk adjustment, and hierarchical condition categories.

Additionally, for next-generation advancements, NLP enables ambient virtual scribe, computational phenotyping and biomarker discovery and population surveillance.

Conclusion

NLP applications are increasing at a fast pace and the technology has all it takes to accelerate customer service. NLP based software now even impact our personal lives as well. According to Gartner, people will have more interactions with chatbots than with their spouses by 2020.

Besides, in the professional ecosystem, as aforementioned, NLP use cases provide a better and basic understanding of this technology can do to maximize productivity, streamline operations, deliver insights and keep up with the competition.