Ranking objects according to different criteria is a central issue in many data-intensive applications. Yet, no existing solution deals with the case of partially specified score aggregation functions (e.g., a weighted sum with no precisely known weight values). We address multi-source top-k queries with constraints (rather than precise values) on the weights. Our solution is instance optimal and provides increased flexibility with negligible overhead wrt classical top-k queries.
Paolo Ciaccia, Davide Martinenghi (2019). Flexible Score Aggregation.
Flexible Score Aggregation
Paolo Ciaccia;
2019
Abstract
Ranking objects according to different criteria is a central issue in many data-intensive applications. Yet, no existing solution deals with the case of partially specified score aggregation functions (e.g., a weighted sum with no precisely known weight values). We address multi-source top-k queries with constraints (rather than precise values) on the weights. Our solution is instance optimal and provides increased flexibility with negligible overhead wrt classical top-k queries.File in questo prodotto:
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