### Table 1: cc Combinators

1997

Cited by 5

### Table 3: Constraints hit by Transactions that T3 is detected as a transaction that might (potentially) violate the constraint A6 even if this will never happen since this transaction only increments the attribute age of a Person instance. This is, indeed, one limitation of this approach. Such a problem will be solved using more powerful techniques, namely, abstract interpretation of programming languages [CC76]. 5 Generation of Enforcement Tests 5.1 Restrictions The problem addressed in this section is to generate, given a constraint, a checking algorithm which guarantees that either the constraint is satis ed at the end of the transaction or the transaction is 13

"... In PAGE 13: ... It can be expressed the following way : Property 1 Given a transaction T and a constraint A, the transaction T might violate the constraint A if and only if (A) \ (T) 6 = ;. Table3 gathers the set of the constraints which might be violated by a given transaction. Note... ..."

### Table 7 defines the C8CTD6CXD3CSC8D6CTD7CTD6DACXD2CV property. If this property holds at a parent node, it also holds at a child, except in the following cases: (1) when the parent operation is a projection not involving the time attributes and whose BWD9D4D0CXCRCPD8CTD7CACTD0CTDACPD2D8 property does not hold; (2) when the parent operation is regular aggregation, where the time attributes are not among the grouping attributes and the aggregation functions used are not among BTCEBZ, CBCDC5,orBVC7CDC6CC; (3) when the parent operation is temporal aggregation; (4) when the parent operation is coalescing and the argument does not have duplicates in snapshots; and (5) when the parent operation is temporal difference and the right argument is the child in question.

"... In PAGE 29: ... Table7 : The C8CTD6CXD3CSC8D6CTD7CTD6DACXD2CV Property Values of an Operation According to its Parent If the property does not hold at the parent operation, the property also does not hold at a child, except in eight cases, namely for the following parent operations: (1) selection with a predicate involving a temporal attribute; (2) projection, if it involves one time attribute or if its BWD9D4D0CXCRCPD8CTD7CACTD0CTDACPD2D8 property holds; (3) regular aggregation, where the time attributes are among the grouping attributes or the aggregation functions are among BTCEBZ, CBCDC5,orBVC7CDC6CC;(4) regular duplicate elimination; (5) regular Cartesian product; (6) temporal Cartesian product if it is not followed by a projection removing the original time attributes; (7) regular difference; and (8) regular union.... ..."

### Table 3.6: Numbers of rules and computation times for various datasets

### Table 1: The conditional probability table for A.

"... In PAGE 4: ...t is not linearly separable. However, there is a NaiveBayes that represents f. Consider a NaiveBayes G on two speci#0Cc nominal attributes A and B, where A = f1; 2; 3g, B = f1; 2; 3g. Table1 is the conditional probability table #28CPT#29 for A, and B has the same CPT as A. It is easy to verify that the classi#0Ccation of G is the same as in Figure 3.... ..."

### Table 2: De nition of CC!

"... In PAGE 6: ...3 The Type System CC! is a formal system for deriving assertions of the form ? ` M : A, read as \M has type A in the context of type assumptions ?". The axioms and rules of derivation for CC! are given in Table2 . We often write ? ` M : A to mean that the indicated assertion is derivable in the formal system, omitting explicit mention of ? when it is the empty context.... ..."

### Table 11. Regression results for CC.

2004

"... In PAGE 20: ... An increase in the average capitalisation of banks generates a decrease in the WCS. The regressions for the CC indicator of contagion ( Table11 ) show results similar to the WCS. The number of cases of contagion tends thus to decrease when moving to a money centre structure or when internationalisation increases.... ..."

Cited by 1

### Table 4. CC and NMI values

"... In PAGE 10: ...2 Results The results show a decent improvement, though not as dramatic of one as might would be hoped. Table4 shows the results of the first experiment where they attempted to recreated a known deformation, displaying correlation coefficients (CC) as well as NMI for both the traditional FFD based method and their new NFFD based method. Table 4.... ..."

### Table 4: Prediction error on missing data.

2007

"... In PAGE 6: ... The quality of the predictions is compared using mean squared error. Table4 displays the prediction errors for a single linear regression model (Global Model), co-clustering, where no attribute information is used (CC), 4Datasets available at http://www.... ..."

Cited by 1