Efficient and Expressive Knowledge Base Completion Using Subgraph Feature Extraction

@inproceedings{Gardner2015EfficientAE,
  title={Efficient and Expressive Knowledge Base Completion Using Subgraph Feature Extraction},
  author={Matt Gardner and Tom Michael Mitchell},
  booktitle={EMNLP},
  year={2015}
}
We explore some of the practicalities of using random walk inference methods, such as the Path Ranking Algorithm (PRA), for the task of knowledge base completion. We show that the random walk probabilities computed (at great expense) by PRA provide no discernible benefit to performance on this task, so they can safely be dropped. This allows us to define a simpler algorithm for generating feature matrices from graphs, which we call subgraph feature extraction (SFE). In addition to being… CONTINUE READING

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