41–50 of 76 posts
On a side note, I love the idea of researchers writing “articles” in this format. No paywall, no complex two-column format, no PDFs. As a researcher myself, I wish this is what my “productivity” was judged upon, I’d probably have a lot more fun and motivation to work and produce!
SQL might be a good fit to model Knowledge Graphs, since FOREIGN KEYs can be named, using the CONSTRAINT constraint_name FOREIGN KEY … syntax. We thus have support to label edges. Nodes = Tables Edges = Foreign keys Edge labels = Foreign key constraint names
Honestly I think people's assumption that graph databases must be better in representing binary relations might be a bit optimistic. After all there's no reason relational databases (named after the n-ary relationships that tables represent) couldn't handle binary relations. The one thing that's definite is that SQL is a bad choice for particular kinds of queries, though most graph databases don't seem to go much fur…
KG are cool, but I haven't find a practical framework of combining simple logical predicates with temporal facts (things that are true at a certain moment in time) and information provenance (the truthiness of information given the origin). There might be ways to encode this information in a hyper graph but they are far from practical.
Wikidata statements (which roughly correspond to the edges in the Knowledge Graph) have quite a bit of Metadata associated with them: they can have refer to sources that state this particular bit of knowledge, they have a so-called rank that allows distinguishing preferred and deprecated statements, and the can be qualified by another statement in the graph. Temporal validity is encoded using a combination of rank an…
On a side note, I love the idea of researchers writing “articles” in this format. No paywall, no complex two-column format, no PDFs. As a researcher myself, I wish this is what my “productivity” was judged upon, I’d probably have a lot more fun and motivation to work and produce!
Two columns is for the reader's benefit - your eyes can keep their place on the page much more easily when jumping half the distance to the beginning of the next line
Earlier quoted context omitted.
This kind of approach is pretty common, including in compute engines like Spark's graphx. I suspect a lot of teams using graph DBs would be better off realizing this: it's good for simple and small problems it does fall down for graphy tasks like multihop joins, connect the dots, and supernodes. So for GB/TBs of that, either you should do those outside the DB, or with an optimized DB. Likewise, not explicitly discuss…
> it does fall down for graphy tasks like multihop joins, connect the dots, and supernodes. These can always be accomplished via recursive SQL queries. Of course any given implementation might be unoptimized for such tasks. But in practice, this kind of network analytics tends to be quite rare anyway. One should note that even inference tasks, that are often thought of as exclusive to the "semantic" or "knowledge" ba…
So this is the ‘semantic web’ from ~15 years ago?
So this is the ‘semantic web’ from ~15 years ago?
Yes because the web is already a kind of knowledge graph but it's mostly written in natural language, and thus it's very hard for machines to traverse and reason about it. The Semantic Web was an attempt to formalize some ways to make the web's inherent knowledge graph nature more explicit and thus easier for programs to understand.
No, because knowledge graphs predated the web by many years and KGs are a bigger topic than just the web.
Knowledge graphs for text (the focus of the article) seem narrowly-scoped since they require "objective" facts and relations to be practical. Capturing the subjective and transient perspective of observations made by multiple observers (which is what we actually have access to) is more complicated. For example, asking the same person the same question may yield different answers based on their mood or other environme…
Knowledge graphs for text (the focus of the article) seem narrowly-scoped since they require "objective" facts and relations to be practical. Capturing the subjective and transient perspective of observations made by multiple observers (which is what we actually have access to) is more complicated. For example, asking the same person the same question may yield different answers based on their mood or other environme…
Recent work suggests it's possible to generate knowledge graphs from large corpi of text encoded with a language model: https://arxiv.org/abs/2010.11967