Stevens, Philip CBlagojevic, RachelPlimmer, BerylLevent Burak Kara and Cindy Grimm2016-02-182016-02-182013978-1-4503-2205-81812-3503https://doi.org/10.1145/2487381.2487383Grouping of strokes into semantically meaningful diagram elements is a difficult problem. Yet such grouping is needed if truly natural sketching is to be supported in intelligent sketch tools. Using a machine learning approach, we propose a number of new paired-stroke features for grouping and evaluate the suitability of a range of algorithms. Our evaluation shows the new features and algorithms produce promising results that are statistically better than the existing machine learning grouper.I.7.5 [Document and Text Processing]Document CaptureGraphics recognition and interpretationI.2.5 [Artificial Intelligence]Programming Languages and SoftwareExpert system tools and techniques. KeywordsDigital Ink recognitiongrouping strokes10.1145/2487381.248738343-52