RULE-BASED JOINS IN HETEROGENEOUS DATABASES

In this paper, the problem of computing joins in heterogeneous databas es is analyzed. Rules are combined with a probabilistic framework to r esolve the data heterogeneity problem. The Entity join operator is def ined to identify and join records across databases. Certain amount of uncertainty is associated with this Entity join model due to the possi bility of wrong matches. While the rule based approach captures the da ta semantics, the probabilistic framework models the uncertainty and p rovides a formal measure of accuracy of the Entity join. Representing the values of mismatched attributes presents a difficult problem becau se the true value of the attribute cannot be identified from the vario us conflicting values. Probabiliistic partial values are used to repre sent these attribute values so that user preferences and reliability o f the data can be taken into account.