Tree edit distance for hierarchical data compatible with HMIL paradigm
Břetislav Šopík, Tomáš Strenáčik · arXiv (Cornell University) · 2022
We define edit distance for hierarchically structured data compatible with the hierarchical multi-instance learning paradigm. Example of such data is dataset represented in JSON format where inner Array objects are interpreted as unordered bags of elements. We prove correct analytical properties of the defined distance.