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Parallel Algorithms for the Generalized Same Generation Query in Deductive Databases

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dc.contributor.author Arman, Nabil
dc.date.accessioned 2017-01-22T06:30:43Z
dc.date.accessioned 2022-05-22T08:26:35Z
dc.date.available 2017-01-22T06:30:43Z
dc.date.available 2022-05-22T08:26:35Z
dc.date.issued 2006
dc.identifier.issn 0972 7272
dc.identifier.uri http://localhost:8080/xmlui/handle/123456789/7764
dc.description.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. en_US
dc.language.iso en_US en_US
dc.subject Deductive Databases, Linear Recursive Rules, Same Generation Query, Parallel Databases en_US
dc.title Parallel Algorithms for the Generalized Same Generation Query in Deductive Databases en_US
dc.type Article en_US

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