Analytics and BI giant SAS has announced an enhanced version of its Text Miner product that includes a patent-pending rules generator to helps organisations crunch through text and other unstructured data to actively learn from and discover meaning in their data.

SAS Text Miner’s new Text Rule Builder node uses predictive and descriptive modeling to automatically generate Boolean rules to better classify documents. These readily interpretable rules can be directly used within SAS Enterprise Content Categorization to classify content in real time. Subject-matter experts can refine machine-generated classification algorithms, resulting in lower costs and greater accuracy.

“Many companies haven’t begun to benefit from valuable enterprise text data,” said Fiona McNeill, Global Product Marketing Manager for SAS Text Analytics.

“Most know that information in-house and in social media must be analysed to bring value. SAS Text Analytics are being used for patient safety in healthcare, digital content performance in the media industry, early-warning systems and citizen intelligence in government and more.”

The new release also offers a new markup matcher that simplifies acquiring Web data for research.