Review on Text Analytics an Approach to Artificial Intelligence

Abstract

: 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 number of text messages sent daily has increased by more than 7%. Younger generations overwhelmingly prefer texting to phone calls. And this is just scratching the surface, as there are many other types of textual data: support tickets, insurance application forms, healthcare records, product descriptions, and many others. Extracting meaning out of this text is an incredibly complicated task since texts may have different contexts and formats. Textual data is usually referred to as unstructured data because it doesn’t have a clear storage format or a predefined data model. Sure, you can put a sentence into an Excel cell. But how would that help you to analyze it? The applications of text analysis are far and wide, from simple automation to advanced interactions between the person inputting the data and the system they interact with. A rudimentary example of that is a chatbot. This paper focuses on how text analytics is a new approach to Artificial Intelligence.