[HN Gopher] Using Topology to Classify Labelled Graphs ___________________________________________________________________ Using Topology to Classify Labelled Graphs Author : Topolomancer Score : 30 points Date : 2020-12-02 18:46 UTC (4 hours ago) (HTM) web link (bastian.rieck.me) (TXT) w3m dump (bastian.rieck.me) | chartpath wrote: | This is a really cool and very smart looking mathematical way of | looking at something that I do with lower-tech taxon labels using | LTREE in Postgres to store the annotations. | | In PG you can do a kind of KNN for things that are X LTREE | degrees away as well as ordering by distance from trigrams of | text. With an ensemble of online learning models for different | blobs of taxa, it is a way to prevent concept drift and give | weights to the different subdomains of training data to fight | bias. | | This kind of topological approach is great. One challenge in SQL | is that class membership can only be so expressive and I have a | nagging desire for slightly more RDF-like edges of | predicates/verbs, but that still feels like overkill to me since | I can already do rule engines with facts based on the labels. | Therefore I end up with class names like "things that verb" or | "things that are verbable" like would be done for naming | interfaces. | | Scanning the paper I don't understand the math well enough (am | more of a code plumber). How would different "types" of edges be | encoded to get past the perceived limitations of class | membership? | nerdponx wrote: | Machine learning (and more generally modeling) on graphs seems | really powerful. Interesting to see continued progress in this | area. ___________________________________________________________________ (page generated 2020-12-02 23:01 UTC)