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NetOwl

NetOwl Entity Extraction Tools

Text and Entity Analytics for Big Data

The explosion of unstructured data has created an information challenge for many organizations. Until now, organizations have not been able to effectively "mine" unstructured data found in email, news, web, social media, or other sources. In addition, fusing unstructured text data with entity data — structured data about people, organizations, places, and things — poses unique challenges for analysis. These massive volumes of text and entity data represent critical information that should be analyzed and exploited for organizations to be competitive in this fast-changing world.

SRA has developed NetOwl®, a suite of rich text and entity analytics products, to analyze Big Data in the forms of text and entity data and turn it into actionable knowledge. NetOwl has been refined over more than a decade of research and development. Our team of researchers and engineers continue to expand NetOwl's capabilities to keep pace with evolving information needs.

Text Analytics Products


NetOwl entity extraction software
NetOwl Extractor

Accurately performs entity extraction from unstructured texts using advanced computational linguistics and natural language processing.

NetOwl document matching software
NetOwl DocMatcher

Intelligently compares and categorizes documents according to user-defined concepts using advanced machine learning and computational linguistics approaches.


NetOwl text mining software
NetOwl TextMiner

Empowers users to find, organize, analyze and mine a large volume of unstructured information using the most advanced text analysis technology available.


Entity Analytics Products


NetOwl name matching software
NetOwl NameMatcher

Accurately and efficiently identifies name variants from large multicultural and multilingual name databases using advanced machine learning and computational linguistic approaches.


NetOwl entity matching software
NetOwl EntityMatcher

Accurately and efficiently performs identity resolution for large multicultural and multilingual entity databases using advanced machine learning and computational linguistic approaches.