Text Analytics: The Convergence of Big Data and Artificial Intelligence

The analysis of the text content in emails, tweets, SMS, blogs, forums and other forms of textual communication is called text analytics. Text analytics is applicable to most industries: it can help analyse millions of emails, using text analytics we can analyse customer's comments and questions in forums, we can perform sentiment analysis using text analytics by measuring positive or negative perceptions of a company, brand, or product. Text Analytics has also been called text mining, and is a subcategory of the Natural Language Processing (NLP) field, which is one of the founding branches of Artificial Intelligence, back in the 1950s, when an interest in understanding text originally developed. Currently Text Analytics is often considered as the next step in Big Data analysis. Text Analytics has a number of subdivisions: Information Extraction, Semantic Web annotated domain's representation, Named Entity Recognition, and many more. Several techniques are currently used and some of them have gained a lot of attention, such as Machine Learning, to show a semi supervised enhancement of systems, but they also present a number of limitations which make them not always the only or the best choice. We conclude with current and near future applications of Text Analytics.