Bootstrapping Uncertainty in Schema Covering

Schema covering is the process of representing large and complex schemas by easily comprehensible common objects. This task is done by identifying a set of common concepts from a repository called concept repository and generating a cover to describe the schema by the concepts. Traditional schema covering approach has two shortcomings: it does not model the uncertainty in the covering process, and it requires user to state an ambiguity constraint which is hard to define. We remedy this problem by incorporating probabilistic model into schema covering to generate probabilistic schema cover. The integrated probabilities not only enhance the coverage of cover results but also eliminate the need of defining the ambiguity parameter. Experiments on real-datasets show the competitive performance of our approach.


Presented at:
29th edition of the Australasian Database Conference, Gold Coast, Australia, May 23-25, 2018
Year:
2018
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 Record created 2018-04-16, last modified 2018-08-14

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