Automatic Taxonomy Generation

Autonomy's Taxonomy Generation feature can automatically and consistently understand and create deep hierarchical contextual taxonomies of information based on conceptual understanding.

Benefits

• Maintain existing taxonomies automatically
• Automates the process of taxonomy generation
• Consistent, objective, accurate and logical taxonomy creation
• Delivers instant visibility of the information assets
• Drive down overheads whilst increasing productivity

Eradicating any human intervention and the errors involved with manual categorization, Autonomy's data agnostic classification capabilities enable organizations to build taxonomies based on any type of data: unstructured, semi-structured, structured data, audio, audio/visual and images. Typically manual taxonomy generation processes miss large areas of commonality in data, missing valuable themes and trends not thought of by the librarians or editors involved.

Clustering or any other conceptual operation can be used as a 'seed' for the process. For example, a cluster can be broken down into a taxonomy automatically. Alternatively a document can be used to find similar information about a subject, and then that area broken down into a taxonomy.

The resulting taxonomy can be used to provide insight into specific areas of the information, provide an overall 'information landscape', or as training material for the automatic categorization that then allows information to be placed into a formally dictated, controlled and named category hierarchy.