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Approximating Certainty in Querying Data and Metadata

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Original languageEnglish
Title of host publicationProceedings of the Sixteenth International Conference on Principles of Knowledge Representation and Reasoning (KR-18)
Number of pages10
Publication statusAccepted/In press - 11 Jul 2018
Event16th International Conference on Principles of Knowledge Representation and Reasoning - Tempe, United States
Duration: 30 Oct 20182 Nov 2018
http://reasoning.eas.asu.edu/kr2018/

Conference

Conference16th International Conference on Principles of Knowledge Representation and Reasoning
Abbreviated titleKR 2018
CountryUnited States
CityTempe
Period30/10/182/11/18
Internet address

Abstract

Metadata, such as mappings or constraints, is used in a variety of scenarios to facilitate query answering; these include data integration and exchange, consistent query answering, and ontology-based data access. A common feature of these scenarios is that data and metadata together produce multiple databases, and answers to queries must be certain, i.e., true in all such databases. This usually incurs prohibitively high complexity outside very restricted classes of queries such as conjunctive queries and their unions.

To overcome this, we propose to approximate such query answering by reducing it to another scenario where multiple databases need to be taken into account, namely incomplete information in databases. For them, well-behaved approximation schemes exist for much larger classes of queries.We give a generic representation of query answering via incomplete data, and show how it works in the scenarios listed above.
We use the connection to show how to effectively approximate several intractable query answering problems, and discuss differences between applying this framework under open and closed world semantics.

Event

16th International Conference on Principles of Knowledge Representation and Reasoning

30/10/182/11/18

Tempe, United States

Event: Conference

ID: 76050470