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Project Description

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.

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Last updated Sat Oct 26 17:00:39 EDT 2019 .