Data Cleaning and Query Answering with Matching Dependencies and Matching Functions

Lecture Notes in Computer Science

2014

Self Cite

Abstract. Matching Dependencies (MDs) are a recent proposal for declarative entity resolution. They are rules that specify, on the basis of similarities satisfied by values in a database, what values should be considered duplicates, and have to be matched. On the basis of a chase-like procedure for MD enforcement, we can obtain clean (duplicate-free), and possibly several, resolved instances. The resolved answers to a query are invariant under the class of resolved instances. Previous work identified classes of queries and sets of MDs for which resolved query answering is tractable, with special emphasis on cyclic sets of MDs. In this work we further investigate the complexity of this problem, identifying intractable cases, and exploring the frontier between tractability and intractability. We concentrate mostly on acyclic sets of MDs. For a special case we obtain a dichotomy result relative to NP-hardness.

“…Alternatives to this chase have been considered [6]. A quite different chase, which applies one MD at a time and uses matching functions, is presented in [5,2].…”

Section: Discussionmentioning

confidence: 99%

Tractable vs. Intractable Cases of Query Answering under Matching Dependencies

Lecture Notes in Computer Science

2014

Self Cite

“…The original semantics was refined in [11,12], including the use of matching functions for matching two attribute values. An alternative refinement of the semantics, which is the one used in this paper, is given in [23,24].…”

Section: Discussionmentioning

confidence: 99%

“…with referential integrity constraints, tuple-generating dependencies in general [1], schema mappings in data exchange [5], etc. A "non-pure" case, that uses matching functions to realize the matchings as prescribed by MDs, is investigated in [11,12,4]. Since there is always an RI [23], there is always an MRI for an instance D wrt M .…”

Section: R(d)mentioning

confidence: 99%

Tractable Cases of Clean Query Answering under Entity Resolution via Matching Dependencies

Lecture Notes in Computer Science

2012

Self Cite

Abstract. Matching Dependencies (MDs) are a recent proposal for declarative entity resolution. They are rules that specify, given the similarities satisfied by values in a database, what values should be considered duplicates, and have to be matched. On the basis of a chase-like procedure for MD enforcement, we can obtain clean (duplicate-free) instances; possibly several of them. The clean answers to queries (which we call the resolved answers) are invariant under the resulting class of instances. Identifying the clean versions of a given instance is generally an intractable problem. In this paper, we show that for a certain class of MDs, the characterization of the clean instances is straightforward. This is an important result, because it leads to tractable cases of resolved query answering. Further tractable cases are derived by making connections with tractable cases of CQA.

“…, b), c). For idempotent, commutative and associative merge functions, all the chase sequences finitely terminate [10,11]. 2…”

Section: Resolved Instancesmentioning

confidence: 99%

“…In [5] entire tuples (records) are merged as opposed to individual attribute values. In [10], the combination of MDs and matching functions is formally developed.…”

Section: Introductionmentioning

confidence: 99%

Matching dependencies: semantics and query answering

Kiringa

2012

Front. Comput. Sci.

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Matching dependencies (MDs) are used to declaratively specify the identification (or matching) of certain attribute values in pairs of database tuples when some similarity conditions on other values are satisfied. Their enforcement can be seen as a natural generalization of entity resolution. In what we call the pure case of MD enforcement, an arbitrary value from the underlying data domain can be used for the value in common that is used for a matching. However, the overall number of changes of attribute values is expected to be kept to a minimum. We investigate this case in terms of semantics and the properties of data cleaning through the enforcement of MDs. We characterize the intended clean instances, and also the clean answers to queries, as those that are invariant under the cleaning process. The complexity of computing clean instances and clean query answering is investigated. Tractable and intractable cases depending on the MDs are identified and characterized.