Journal
INFORMATION RETRIEVAL JOURNAL
Volume 22, Issue 3-4, Pages 232-255Publisher
SPRINGER
DOI: 10.1007/s10791-018-9342-1
Keywords
Set expansion; Cold start recommendation; Content based recommendation; Variational autoencoder; Product of experts (POE); Unsupervised learning
Categories
Funding
- Defense Advanced Research Projects Agency [FA8750-13-2-001]
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We propose Neural variational set expansion to extract actionable information from a noisy knowledge graph (KG) and propose a general approach for increasing the interpretability of recommendation systems. We demonstrate the usefulness of applying a variational autoencoder to the Entity set expansion task based on a realistic automatically generated KG.
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