Learning to parse hierarchical lists and outlines using conditional random fields

Handwritten notes are complex structures which include blocks of text, drawings, and annotations. The main challenge for the newly emerging tablet computer is to provide high-level tools for editing and authoring handwritten documents using a natural interface. One frequent component of natural notes are lists and hierarchical outlines which correspond directly to the bulleted lists and itemized structures in conventional text editing tools. We present a system which automatically recognizes lists and hierarchical outlines in handwritten notes, and then computes the correct structure. This inferred structure provides the foundation for new user interfaces and facilitates the importation of handwritten notes into conventional editing tools.