Ranking Companion integrates six complementary item-selection methods with model-driven active learning in a visual analytics interface to support iterative personalized ranking creation via known-item judgments.
Personalized Visual-Interactive Music Classification,
2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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2026 2representative citing papers
Data points genuinely similar to multiple dissimilar neighborhoods are detected as local articulation points of a sparsified high-dimensional graph and split into multiple projected copies, one per neighborhood.
citing papers explorer
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Ranking Companion: A Visual Analytics Approach to Item-Based Ranking with Hybrid Item Selection
Ranking Companion integrates six complementary item-selection methods with model-driven active learning in a visual analytics interface to support iterative personalized ranking creation via known-item judgments.
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When One Point Is Not Enough: Addressing Ambiguous Instances in Dimensionality Reduction by Splitting
Data points genuinely similar to multiple dissimilar neighborhoods are detected as local articulation points of a sparsified high-dimensional graph and split into multiple projected copies, one per neighborhood.