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Text analytics and natural language processing

Both text analytics and natural language processing (NLP) incorporate AI and use techniques to gain a deep understanding of language. Text analyticsis the basis of intelligent search as well as being a powerful tool for analyzing large volumes of information. It was used extensively by scientists and pharmaceutical companies to analyze information related to COVID-19 and emerging news about its variants. As of the end of 2020, tens of thousands of papers had been published on the topic, and the ability of text analytics to summarize findings, discover patterns, and link articles to clinical findings was a vital element in keeping pace with developments in the field.

In May 2020, SAS launched a free visual text analytics environment that uses AI and machine learning to search research articles on COVID-19. Based on SAS Viya, it uses SAS Visual Text Analytics and SAS Visual Data Mining and Machine Learning to support exploration of data in the COVID-19 Open Research Dataset (CORD-19). SAS has added models that allow extraction and visualization of quantitative data.

In addition to the uptick in usage for research on COVID, text analytics continues to be used for analysis of social media, emails, and other content to monitor customer sentiment and predict customer behavior, detect fraud, and track compliance. Microsoft includes text analytics as part of its Azure Cognitive Services, which also provides speech-to-text services. These services allow small companies the option of using technologies that they would not otherwise be able to include in their infrastructure.

NLP enables computers to interpret the intent of spoken or written language and respond appropriately. Some researchers had predicted a slowdownin the market for NLP in 2020 because industries such as manufacturing, transportation and logistics, and some consumer goods producers were impacted by supply chain issues that reduced customer interactions. Others have cited its role in improving efficiency as driving growth, and foresee greater growth. In general, however, the predictions for the upcoming years are positive.

Chatbots and interactive virtual assistants are showing dynamic growth, and they produce major business benefits in terms of cost savings. According to Juniper Research, the savings across retail, banking, and healthcare could reach $11 billion by 2023. Although it is certain that this technology will see increasing use, research on customer response is mixed; some research indicates that customers do not care where the information is coming from as long as they get what they need, while other research reveals considerable customer dissatisfaction with this technology.

The global market for text analytics was estimated by Mordor Intelligence at $5.5 billion in 2020, with a 5-year predicted growth rate of 17% per year to reach about $15 billion by 2026.

Mordor Intelligence estimated the NLP market at $13 billion in 2020 and predicts growth of slightly more than 20% per year through 2026, to reach $42 billion. MarketsandMarkets predicts comparable growth of 20% per year for NLP, rising from $11.6 billion in 2020 to $35.1 billion by 2026.

What’s ahead

Whether due to well-thought-out digital transformation initiatives or a rapid response to the onset of new work-from-home strategies caused by the pandemic, these technologies are expected to carry forward and evolve. Increased use of collaboration, cloud technology, AI, and text analytics and NLP, as well as graphs databases (see previous page), are among the areas gaining ground and enriching the opportunities for advancement through knowledge management.

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