DINOSAUR augments ANN indices with sampled embeddings to marginalize uncertainty, recovering standard retrieval at zero uncertainty while expanding coverage for uncertain items.
ACM Transactions on Information Systems 40, 1–22
2 Pith papers cite this work. Polarity classification is still indexing.
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A late-fusion model of CF, RL bandit, and TOPSIS achieves NDCG@5=0.3040 on JobHop (outperforming baselines) but remains competitive without significant gains on Karrierewege, with the bandit branch deactivating in persistence-dominated data.
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Distributional Approximate Nearest Neighbour Search for Uncertainty-Aware Retrieval
DINOSAUR augments ANN indices with sampled embeddings to marginalize uncertainty, recovering standard retrieval at zero uncertainty while expanding coverage for uncertain items.
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An Interpretable CF-RL-TOPSIS Fusion Model for Skills-Aware Talent Recommendation
A late-fusion model of CF, RL bandit, and TOPSIS achieves NDCG@5=0.3040 on JobHop (outperforming baselines) but remains competitive without significant gains on Karrierewege, with the bandit branch deactivating in persistence-dominated data.