What is text analysis?

Text analysis is the process of transforming unstructured text data into meaningful data for analysis, so as to measure customer opinions, product comments and feedback, and provide search tools, sentiment analysis and entity modeling to support fact-based decision-making. Text analysis uses many languages, statistics and machine learning techniques. Text analysis includes the process of retrieving information from unstructured data, constructing input text to obtain patterns and trends, and evaluating and interpreting output data. It also includes lexical analysis, classification, clustering, pattern recognition, labeling, annotation, information extraction, link and association analysis, visualization and predictive analysis.

? Analysis determines keywords, topics, categories, semantics and tags from millions of text data with different files and formats. The term text analysis is roughly equivalent to text mining.

? Text analysis software solutions provide tools, servers, application programs based on analysis algorithms and data mining and extraction tools to transform unstructured data into meaningful data for analysis. Outputs (extracted entities, facts and relationships) are usually stored in relationships, XML and other data warehouse applications for analysis by other tools, such as business intelligence tools or big data analysis or predictive analysis tools.

? Big data analysis, data mining, text analysis and statistical data provide business users with the function of creating intelligent forecasts by discovering patterns and relationships in structured and unstructured data.