A Knowledge Based Approach to Assisting in Data Quality Judgement

Cover A Knowledge Based Approach to Assisting in Data Quality Judgement
A Knowledge Based Approach to Assisting in Data Quality Judgement
Yeona Jang
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This allows removing q-. =Vj from Q, if both q^:=v^ and . -u are elements in Q. Continue the process of removing dominated quality parameters, until no pair of the quality parameters in Q are related in the dominance relation. Let il' denote the modified Q produced at the end of this removal process. The quality merge of the quality parameters in Q' is the corresponding irreducible quality-merge statement of e, and the algorithm returns ©(Q). It is proven in (Jang & Wang, 1991) that Algorithm ...Q-Reduction shown in Figure 2 always results in a unique output in the first-order data-quality reasoner, in that all dominance relations must be first-order.
3. 2. Algorithm Q-Merge When presented with an instance of the quality-estimating problem (®{q-^, q2, --, q„), DR) for some integer n, Algorithm Q-Merge first instantiates the given quality-merge statement, accordingly. The instantiated quality-merge statement is then reduced until the reduction process results m another instantiated quality-merge statement which cannot be reduced any further (using Q-Reduction).


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