3 ms·
"without the motive power of capital, things move slowly" slowly?! We've amassed huge collections of detailed knowledge in mere decades, and it's all searchabl
by jeffdavis 11y ago
"without the motive power of capital, things move slowly"
slowly?! We've amassed huge collections of detailed knowledge in mere decades, and it's all searchable and discoverable.
"not one big pool of knowledge"
The real fantasy is centralization and taxonomies of everything. Distributed isn't a lazy thing we've settled on; it's the best approach. Each island grows about as far as it makes sense, and connects to other islands where it makes sense.
Sure, it may be imperfect and some datasets are hidden in corporations, but open data is certainly a healthy and growing ecosystem in no danger of extinction.
- 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.