Abstract
Today, probabilistic databases (PDB) become helpful in several application areas. In the context of cleaning a single PDB or integrating multiple PDBs, duplicate tuples need to be merged. A basic approach for merging probabilistic tuples is simply to build the union of their sets of possible instances. In a merging process, however, often additional domain knowledge or user expertise is available. For that reason, in this paper we extend the basic approach with aggregation functions, knowledge rules, and instance weights for incorporating external knowledge in the merging process.
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Panse, F., Ritter, N. (2011). Incorporating Domain Knowledge and User Expertise in Probabilistic Tuple Merging. In: Benferhat, S., Grant, J. (eds) Scalable Uncertainty Management. SUM 2011. Lecture Notes in Computer Science(), vol 6929. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23963-2_23
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DOI: https://doi.org/10.1007/978-3-642-23963-2_23
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