Xiang Lian
Yincheng Lin
Lei Chen
ABSTRACT
Due to the ubiquitous data uncertainty in many emerging real applications, efficient management of probabilistic databases has become an increasingly important yet challenging problem. In particular, one fundamental task of data management is to identify those unreliable data in the probabilistic database that violate integrity constraints (e.g., functional dependencies), and then quickly resolve data inconsistencies. In this paper, we formulate and tackle an important problem of repairing inconsistent probabilistic databases efficiently by value modification. Specifically, we propose a repair semantic, namely possible-world-oriented repair (PW-repair), which partitions possible worlds into several disjoint groups, and repairs these groups individually with minimum repair costs. Due to the intractable result that finding such a PW-repair strategy is NP-complete, we carefully design a heuristic-based greedy approach for PW-repair, which can efficiently obtain an effective repair of the inconsistent probabilistic database. Through extensive experiments, we show that our approach can achieve the efficiency and effectiveness of the repair on inconsistent probabilistic data.
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Index Terms
- Cost-efficient repair in inconsistent probabilistic databases
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