Learning to Parse Hierarchical Lists and Outlines Using Conditional Random Fields

Authors:
Ming Ye;Paul Viola
Affiliations:
Microsoft Corporation;Microsoft Corporation
Venue:
IWFHR '04 Proceedings of the Ninth International Workshop on Frontiers in Handwriting Recognition
Year:
2004

Citing 0
Cited 5

Grouping Text Lines in Freeform Handwritten Notes

ICDAR '05 Proceedings of the Eighth International Conference on Document Analysis and Recognition
Learning Diagram Parts with Hidden Random Fields

ICDAR '05 Proceedings of the Eighth International Conference on Document Analysis and Recognition
Revealing the structure of medical dictations with conditional random fields

EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Parsing ink annotations on heterogeneous documents

SBM'06 Proceedings of the Third Eurographics conference on Sketch-Based Interfaces and Modeling
Contextual text/non-text stroke classification in online handwritten notes with conditional random fields

Pattern Recognition

Quantified Score

Hi-index	0.00

Visualization

Abstract

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.