Text Mining

NetOwl TextMiner integrates all text analytics capabilities of NetOwl Extractor, including entity extraction, relationship, and event extraction, sentiment analysis, text categorization, and geotagging into all-encompassing text mining software.  Extractor output is stored in Elasticsearch for a variety of intelligent search and analytic capabilities.  The combination of Elasticsearch and NetOwl provides fast and scalable real-time text analysis for Big Data.

TextMiner’s Web-based UI is an easy to use and configurable text analytics tool for different analysis scenarios and enables users to gain quick access to all and only high-value information derived from a vast amount of texts.

NetOwl TextMiner automatically constructs a comprehensive biography of a person, organization, place, or other entity types from multiple documents. A person biography might contain information such as aliases, age, titles, family members, associates, affiliated organization, etc. that are found in the texts NetOwl analyzed.  An organization biography might include its key executives, subsidiaries, headquarters locations, and so on.

All of the linked entities are hyperlinked to their own profile page, allowing the user to walk through the network of connections between entities.

NetOwl’s sentiment analysis output can be viewed in TextMiner in multiple ways. All sentiment information associated with a specific entity can be shown in bar and pie charts.  It can be also shown across a timeline.  Additionally most frequent sentiment-bearing terms associated with the entity are also displayed for each sentiment type.

For example, when viewing sentiments toward a company, one may find sentiments about not only the company itself but also sentiments about specific aspects of the company, such as the price of its products, its customer service, or other aspects of its business.