Abstract:
The intelligence of traditional database systems can be improved by recursion. Using recursion, relational database systems are extended into knowledgebase
systems (deductive database systems). Linear recursion is the most frequently found type of recursion in deductive databases. Deductive databases queries are
computationally intensive and lend themselves naturally to parallelization to speed up the solution of such queries. In this paper, parallel algorithms to solve the generalized
fully and partially instantiated forms of the same generation query in deductive databases are presented. The algorithms use special data structures, namely, a special matrix that stores paths from source nodes of the graph representing a two-attribute normalized database relation to all nodes reachable from these source nodes,
and a reverse matrix that stores paths from any node to all source nodes related to that node.
