Automating XML mark-up using a two stage machine learning technique

We introduce a novel two-stage automatic XML mark-up system, which combines the WEBSOM approach to document categorisation in conjunction with the C5 inductive learning algorithm. The WEBSOM method clusters the XML marked-up documents such that semantically similar documents lie close together on a Self-Organising Map (SOM). The C5 algorithm automatically learns and applies mark-up rules derived from the nearest SOM neighbours of an unmarked document. The system learns from mark-up errors to improve accuracy. The automatically marked-up documents produced by the system are also categorized on the Self-Organizing Map, to further refine SOM's document coverage