Auto-Classification

MindSet, the hybrid learn-by-example and rules classification and routing engine behind Attensity Respond, is also available as a standalone component for custom routing and classification applications.

MindSet’s Categorization Engine learns from very small document sets, understanding the content of documents and sorting them by topics, relevancy, user profiles, and keywords, based on your dynamic rules for classification. It reliably detects fully or partially identical texts, and can purge or filter stored data.

It identifies numerous languages, even with just a single sentence, including Arabic, Hebrew, Cyrillic alphabet based languages and double-byte Asian languages, such as Korean and Chinese.

MindSet also recognizes and displays relevant relationships between data points and divides the results into contextual groups, while its clustering functionality classifies unstructured information into thematic groups, identifying the major topics in documents, and recommends structure for classification.