Structure the Unstructured
Text Mining, also known as Text Analysis or Data Mining, is the use of varied techniques to semantically analyze and automatically enrich data in large data volumes and then search for hidden patterns and relationships. ZyLAB’s solutions use information extraction techniques from the field of text mining to detect semantic entities such as persons, companies, organizations, locations, amounts, time notions, and other basic entities. By combining these entities we can detect attributes and properties, recognize relations, facts and even events. Text mining identifies and highlights information from patterns and semantic relations that were previously unknown.
Text mining makes it is even possible to detect sentiments, emotions and high-level concepts. All this additional information can be used to organize the data by facets or data visualization to present the data in a clear and organized way to the end user.
By extracting the right information and using the appropriate visualizations, it is often possible to align the data based on the business application. This way the most common answers to the search questions are much easier to find and sometimes even directly clear from the data.
Facets showing automatically extracted Organizations, Persons and Negative Sentiments