DataFunTalk
Jul 3, 2019 · Artificial Intelligence
Improving Recommendation Diversity with Determinantal Point Processes and Greedy Optimization
The article explains how recommendation systems balance exploitation and exploration, introduces diversity metrics such as temporal, spatial, and coverage, and presents a determinantal point process (DPP) based algorithm accelerated by Cholesky decomposition and greedy inference, demonstrating significant speedups and improved relevance‑diversity trade‑offs in experiments.
Recommendation systemscholesky decompositiondeterminantal point process
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