Abstract: Technologies are disclosed for grouping strokes of digital ink. The disclosed technologies receive a new stroke of digital ink and, responsive thereto, identify groups of strokes that are candidates for receiving the new stroke. Heuristics are computed for one of the candidate groups and for the new stroke. A confidence value is computed for the new stroke based upon the heuristics for the new stroke and the candidate group. If the confidence value exceeds a confidence threshold, which can be user-adjustable, the new stroke of digital ink is added to the candidate group. This process can then be repeated for other candidate groups until a group is found for the new stroke. If no group is found, a new group can be created for the new stroke. A machine learning model can also generate weights for use in computing confidence values.

Abstract: Technologies are disclosed for grouping strokes of digital ink. The disclosed technologies receive a new stroke of digital ink and, responsive thereto, identify groups of strokes that are candidates for receiving the new stroke. Heuristics are computed for one of the candidate groups and for the new stroke. A confidence value is computed for the new stroke based upon the heuristics for the new stroke and the candidate group. If the confidence value exceeds a confidence threshold, which can be user-adjustable, the new stroke of digital ink is added to the candidate group. This process can then be repeated for other candidate groups until a group is found for the new stroke. If no group is found, a new group can be created for the new stroke. A machine learning model can also generate weights for use in computing confidence values.