Text Analytics an Approach to AI
Vaishnavi D. Fate, Akshay Deshmukh, H.N. Watane · Journal of Emerging Technologies and Innovative Research · 2021
Text analytics supports organizations in managing unstructured information, identifying connections and relationships in information, and in extracting relevant entities to improve knowledge management activities. For the past decade, the amount of text messages sent monthly has increased by more than 7,700%. Younger generations overwhelmingly prefer texting to phone calls. And this is often scratching the surface, as there are many other sorts of textual data: support tickets, insurance application forms, healthcare records, product descriptions, and plenty of others. Extracting meaning out of this text is an incredibly difficult task since texts may have different contexts and formats. Textual data is sometimes remarked as unstructured data because it doesn’t have a transparent storage format or a predefined data model. Sure, you could put a sentence into an Excel cell. But how would that facilitate you to study it? The applications of text analysis are far and wide, from simple automation to advanced interactions between the person inputting the data and also the system they interact with. A fundamental example of that is a chatbot. This paper emphasis on how text analytics is a new approach to Artificial Intelligence.