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.
2019
Proceedings of the 27th Italian Symposium on Advanced Database Systems
5.1
5.8
Paolo Ciaccia, Davide Martinenghi (2019). Flexible Score Aggregation.
Paolo Ciaccia; Davide Martinenghi
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/738664
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