3 ms·
If someone is it's probably pretty niche. RDF is a bit simpler and still not commonly used due to its perceived complexity compared to RDBMS tables or JSON.
by cess11 3y ago
If someone is it's probably pretty niche. RDF is a bit simpler and still not commonly used due to its perceived complexity compared to RDBMS tables or JSON.
- nl 3y agoThis completely misunderstands what this is. In this context "knowledge graph" means a representation of knowledge independent of it's serialization format (ie, RDF vs whatever). It's usable wherever you have a key value (key:value of relationship) or a triple (key:relationship:something). This is probably 85% of everything that is stored in a database, with the exception being paths that vary enough that you can't use the path as a key or relationship. In particular, most trees are suitable if you use collapse the path down to a single relationship. I've done a bunch of work on graph embedding. They are very effective for use in anything that can be thought of as a recommendation system ("this person would like these books") or similarity ("this person is similar to these people"). Back when I was working on them I found Starspace wonderfully easy and effective: https://github.com/facebookresearch/StarSpace https://github.com/facebookresearch/StarSpace
- cess11 3y agoI didn't compare RDF directly to the technique in TFA.
- DrDroop 3y agoIt is wrong the call this a "complete misunderstanding" as the paper clearly deals with triplets and formulates a different encoding scheme for entities and relations. Ok, so it is not RDF or even hyper graphs but it is dealing with a graph structure.
- nl 3y agoSure, but as I explain almost everything can fit that structure. The misunderstanding is the " probably pretty niche" part since related techniques (graph embedding generally) are so widely used.