TY - JOUR AU - Coen, Michael AU - Ansari, M. AU - Fillmore, Nathanael PY - 2011/08/04 Y2 - 2024/03/29 TI - Learning from Spatial Overlap JF - Proceedings of the AAAI Conference on Artificial Intelligence JA - AAAI VL - 25 IS - 1 SE - AAAI Technical Track: Knowledge Representation and Reasoning DO - 10.1609/aaai.v25i1.7859 UR - https://ojs.aaai.org/index.php/AAAI/article/view/7859 SP - 177-182 AB - <p> This paper explores a new measure of similarity between point sets in arbitrary metric spaces. The measure is based on the spatial overlap of the &ldquo;shapes&rdquo; and &ldquo;densities&rdquo; of these point sets. It is applicable in any domain where point sets are a natural representation for data. Specifically, we show examples of its use in natural language processing, object recognition in images and point set classification. We provide a geometric interpretation of this measure and show that it is well-motivated, intuitive, parameter-free, and straightforward to use. We further demonstrate that it is computationally tractable and applicable to both supervised and unsupervised learning problems. </p> ER -