### Table 5: General rules

1989

"... In PAGE 14: ... general rules for (higher order) intuitionistic logic, where variables range over values, while terms denotes computations (see Table5 for the most relevant rules)10 the basic inference rules for computational models (see Table 6) the inference rules for product types (see Table 7) the inference rules for functional types (see Table 8) Remark 4.1 A comparison among c-, v- and p-calculus shows that: the v-calculus proves less equivalences between -terms, e.... ..."

Cited by 369

### Table 5: General rules

1989

"... In PAGE 14: ... general rules for (higher order) intuitionistic logic, where variables range over values, while terms denotes computations (see Table5 for the most relevant rules)10 the basic inference rules for computational models (see Table 6) the inference rules for product types (see Table 7) the inference rules for functional types (see Table 8) Remark 4.1 A comparison among c-, v- and p-calculus shows that: the v-calculus proves less equivalences between -terms, e.... ..."

Cited by 369

### Table 1 PHB mapping restriction rules Application Rule 1 Rule 2 Rule 3 Rule 4

2001

"... In PAGE 3: ... The PHB mapping management active policies are local to each PoP, selecting the most important connections that can use the higher priority traffic classes, and downgrading the least important ones, according to the network load. Table1 shows four possible restriction rules. Rule 1 makes no restriction.... ..."

Cited by 4

### Table 7: Partially Compressed Decision Table Rules

1997

"... In PAGE 25: ... As an example of the difference, consider a cost minimization problem where the knowledge source is a decision table. For illustration purposes, let us use the simple decision table depicted in Table7 . A joint approach such as [MM78] can use this decision table to find the optimal solution.... In PAGE 25: ... A separate approach requires that decision table reveal all possible compressed rules. Table7 is only partially compressed because it is missing a compressed rule1: I1=F, I2=F, I3=- (dash). The search space is larger for partially compressed decision tables because missing or implied rules must be discovered in the search process, but the knowledge source is easier to generate.... ..."

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### Table 9 Inference rules

1995

Cited by 258

### Table 4: Comparison in number of rules Datasets strong rules correlated rules

2004

"... In PAGE 5: ... The results are not presented in the table. Table4 shows the drastic reduction in rule number when the correlation measure is used to derive interesting rules. Under the second column in the table, the approximate num- ber of rules derived in the support-confidence framework are given.... ..."

Cited by 2

### Table 6: General Inference Rules

1991

"... In PAGE 12: ...7 Given a signature for the programming language, let be the signature for the metalanguage with the same base types and a function p: 1 ! T 2 for each command p: 1 * 2 in . The translation from programs over to terms over is de ned by induction on raw programs: x [x]T (let x1(e1 in e2) (letT x1(e1 in e2 ) p(e1) (letT x(e1 in p(x)) [e] [e ]T (e) (letT x(e in x) The inference rules for deriving equivalence and existence assertions of the simple programming language can be partitioned as follows: general rules (see Table6 ) for terms denoting computations, but with variables ranging over values; these rules replace those of Table 2 for many sorted monadic equational logic rules capturing the properties of type- and term-constructors (see Table 7) after interpretation of the programming language; these rules replace the additional rules for the metalanguage given in Table 4.... ..."

Cited by 585

### Table 10: Inference Rules of the Metalanguage

1991

"... In PAGE 18: ...7 (metalanguage) An interpretation [[ ]] of the metalanguage in a category C with terminal object !A: A ! 1, binary products A1;A2 i : A1 A2 ! Ai and a strong monad (T; ; ; t) is parametric in an interpretation of the symbols in the signature and is de ned by induction on the derivation of well-formedness for types (see Table 8), terms and equations (see Table 9). Finite products A1;:::;An i : A1 : : : An ! Ai used to interpret contexts and variables are de ned by induction on n: 0 A1 : : : A0 = 1 n + 1 A1 : : : An+1 = (A1 : : : An) An+1 { A1;:::;An+1 n+1 = (A1 ::: An);An+1 2 { A1;:::;An+1 i = (A1 ::: An);An+1 1 ; A1;:::;An i The inference rules for the metalanguage (see Table10 ) are divided into three groups: general rules for many sorted equational logic rules for nite products rules for T... ..."

Cited by 585