The customization process of using this module typically involves obtaining a collection of pre-categorized documents from the organization. Pangea trains its deep neural networks to recognize the features of each document and the difference with other documents. This creates a “knowledge graph” representation, training a categorizer to recognize a particular knowledge set. This trained set is saved and queries can be set against it.
There are several ways to carry out the queries. The top-level Text Classification and Categorizer module provides an umbrella class for top level category classifier operations, but you may use the interfaces of the individual classes in each class.
Our semantic tool automatically classifies documents by content and organizes them within general categories such as Eurovoc or it can be customized to your organization’s structure, terminology and processes. The Categories can be Legal, Compliance, Human Resources, Research and Development, Accounts and Finance, Reports (Sales, Management, etc.), Customer Feedback, Newsletters, and many more. The definition of categories is a free user’s choice not restricted by categorization algorithms.