ontological-pathfinding
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Ontological Pathfinding (OP) is a scalable first-order rule mining algorithm.
It achieves scalability via a series of parallelization and optimization
techniques: a relational knowledge base model to apply inference rules in
batches, a new rule mining algorithm that parallelizes the join queries, a
novel partitioning algorithm to break the mining tasks into smaller independent
sub-tasks, and a pruning strategy to eliminate unsound and resource-consuming
rules before applying them.
Combining these techniques, OP is the first rule
mining algorithm that mines 36,625 inference rules from Freebase, the largest
Public knowledge base with 112 million entities and 388 million facts.