Data Cleaning and Query Answering with Matching Dependencies and Matching Functions
Matching dependencies were recently introduced as declarative rules for data cleaning and entity resolution. Enforcing a matching dependency on a database instance identifies the values of some attributes for two tuples, provided that the values of some other attributes are sufficiently similar. Assuming the existence of matching functions for making two attribute values equal, we formally introduce the process of cleaning an instance using matching dependencies, as a chase-like procedure. We show that matching functions naturally introduce a lattice structure on attribute domains, and a partial order of semantic domination between instances. Using the latter, we define the semantics of clean query answering in terms of certain/possible answers as the greatest lower bound/least upper bound of all possible answers obtained from the clean instances. We show that clean query answering is intractable in general. Then we study queries that behave monotonically w. r. t. semantic domination order, and show that we can provide an under/over approximation for clean answers to monotone queries. Moreover, non-monotone positive queries can be relaxed into monotone queries.
|Keywords||Certain answer, Data cleaning, Databases, Entity resolution, Lattice, Matching dependency, Matching function, Possible answer, Query relaxation, Semantic domination|
|Journal||Theory of Computing Systems|
Bertossi, L, Kolahi, S. (Solmaz), & Lakshmanan, L.V.S. (Laks V.S.). (2013). Data Cleaning and Query Answering with Matching Dependencies and Matching Functions. Theory of Computing Systems, 52(3), 441–482. doi:10.1007/s00224-012-9402-7