Deductive Databases and Their Applications by Robert Colomb

By Robert Colomb

An introductory textual content aimed toward people with an undergraduate wisdom of database & info structures describing the origins of deductive database in Prolog, & then is going directly to examine the most deductive database paradigm - the datalog version.

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All the rest are produced entirely by rule A2. 3 IDB: A1: ancestor(Older, Younger) :- parent(Older, Younger). A2: ancestor(Older, Younger) :- parent(Older, Middle), ancestor(Middle, Younger). Δ1 = ancestor(bill, peter). ancestor(bill, paul). ancestor(mary, peter). ancestor(mary, paul). ancestor(paul, John). ancestor(paul, sue). ancestor(sue, alice). ancestor(sue, eva). Δ2 = ancestor(bill, John). ancestor(bill, sue). ancestor(mary, John). ancestor(mary, sue). ancestor(paul, alice). ancestor(paul, eva).

Furthermore, in most applications a given node can appear only once in a path. If the path represents a cycle, generally at most one node appears twice. The following predicates illustrate how a path is formed in the various special cases of graph which we have considered. 39). 40). 41) where the predicate member is true if I is a member of the list PathSoFar. 10. One of these special graph structures, the tree, is an example of a (homogeneous) hierarchical data structure. 3, if we start with a node instance R which is the root of a (sub)tree, then R can be interpreted as the name of a set of nodes which are the target of arcs whose source is R.

The first step is to compute a superset of new tuples, which we will designate Δ′. If a clause h has only one IDB subgoal p, and a conjunction of EDB subgoals e, then the new tuples of h are If h has several IDB subgoals p1, p2,…, pn, then the new tuples of h are At each stage, only the clauses of Δ′h for which Δp, is non-empty need be evaluated. Further, the other subgoals have all their relevant tuples already computed in the accumulating perfect model, so can be treated similarly to EDB predicates.

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