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> The real fantasy is centralization and taxonomies of everything Precisely. Currently there are plenty of graph-based databases to choose from - GraphDB, Aran
by anon4 11y ago
> The real fantasy is centralization and taxonomies of everything
Precisely. Currently there are plenty of graph-based databases to choose from - GraphDB, ArangoDB, Neo4j, Allegro, etc etc. They are all pretty good, and some also support rule-based inferencing, i.e. you can put a rule in the database like "if X is a person and belongs to team Y and the manager for team Y is Z, then Z is X's manager".
Systems like that have a few disadvantages:
1. They absolutely implicitly trust all data you put in them. If in the above example you add Z as a member to team Y, then it will infer that Z is Z's manager.
2. You cannot assert negatives, nor can you search based on negative predicates.
The first is the absolute killer for such technologies if you try to deploy them internet-wide and gather "data" from any random source publishing RDF documents.
- alex_hirner 11y agoad 1: why not attach a credibility score to relations (probably aggregated from multiple sources) and query against those too?
- wolfgke 11y agoWhat inference rules for unreliable data do you suggest?
- ZenPsycho 11y agois there something wrong with inductive logic? https://en.wikipedia.org/wiki/Inductive_reasoning https://en.wikipedia.org/wiki/Inductive_reasoning
- nl 11y agoInductive logic needs an implementation. These are things like Bayes Nets, Inference using Gibbs sampling, PSL, etc. You can sorta, mostly get them to work if you have a clean graph, and are prepared to spend a long time debugging. The problem is that no one has managed to get them to work well enough to be useful on dirty, web-scale knowledge graphs.
- alex_hirner 11y agoProbabalistic Soft Logic, Markov Logic, Natural Soft Logic (https://youtu.be/EX1hKxePxkk?t=23m00s https://youtu.be/EX1hKxePxkk?t=23m00s). Despite those operate on the semantic level to credit/discredit drawn inferences and treat phrases at face value, I assume you can factor in credibility from sources as well.