Efficient management of transitive relationships in large data and knowledge bases

Rakesh Agrawal, Alexander Borgida, H. V. Jagadish

Research output: Contribution to journalArticlepeer-review

289 Scopus citations

Abstract

We argue that accessing the transitive closure of relationships is an important component of both databases and knowledge representation systems in Artificial Intelligence. The demands for efficient access and management of large relationships motivate the need for explicitly storing the transitive closure in a compressed and local way, while allowing updates to the base relation to be propagated incrementally. We present a transitive closure compression technique, based on labeling spanning trees with numeric intervals, and provide both analytical and empirical evidence of its efficacy, including a proof of optimality.

Original languageEnglish (US)
Pages (from-to)253-262
Number of pages10
JournalACM SIGMOD Record
Volume18
Issue number2
DOIs
StatePublished - Jun 1 1989

All Science Journal Classification (ASJC) codes

  • Software
  • Information Systems

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