Cortex Intelligence developed – and proceeds in the improvement of – text mining components that can be utilized solo or in synergy with unstructured information analysis tools.

It is important to understand that these components, when used together, guarantee the highest quality in the text analysis, since that way the content can be “interpreted” in more detail.

Contextual Categorization: goes beyond the simplistic “key-words” approach, discovering automatically the best strategy to classify a mass of texts in categories that reflect themes of specific interest to the user (e.g. macroeconomics, regulatory aspects, politics, etc).

Synopses: creates automatic text synopses, taking into consideration the most relevant sentences in the content, performing contractions in its structure if necessary.

Entity Extractor: automatically recognizes organizations, people, places, dates and cited values in text based documents, extracting also the available knowledge about these from the text itself.

Reputation Analysis: recognizes qualiffiers associated to entities and identifies whether they are positive or negative.

Relationship Extractor: recognizes relationships between organizations, people, office positions and themes, identifiying the nature and strength of these relationships.

Fact Extractor: Through previously recognized patterns, the system can identify the occurrence of an event, a new product launch, the acquisistion of a company or even an executive hiring.

Disambiguation: reduces interpretation errors in searches and text categorization when identifying not only a term of interest but also the context to which it is associated.

Web Collection Robots: navigates the desired sites on the internet and captures with precision the desired information.