A Framework for Join Pattern Indexing in Intelligent Database Systems

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalNot applicablepeer-review

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Original languageEnglish
Pages (from-to)941-947
Journal / PublicationIEEE Transactions on Knowledge and Data Engineering
Issue number6
Publication statusPublished - Dec 1995
Externally publishedYes


In intelligent database systems, knowledge-directed inference often derives large amounts of data, and the efficiency of query processing in these systems depends upon how the derived data are maintained. This paper focuses on situations where the rule is conditional on a join of multiple data objects (relations) and the rule-derived data are materialized to reduce the overall query processing costs. We develop an indexing technique based on a unique construct called join pattern relation. Several pattern redundancy reduction methods are also introduced to minimize the overhead cost of join indexing. © 1995 IEEE

Research Area(s)

  • data materialization, indexing, Intelligent databases, join, rule processing, rule-based systems