Mining RDF metadata for generalized association rules: knowledge discovery in the semantic web era

ABSTRACT

In this paper, we present a novel frequent generalized pattern mining algorithm, called GP-Close, for mining generalized associations from RDF metadata. To solve the over-generalization problem encountered by existing methods, GP-Close employs the notion of emphgeneralization closure for systematic over-generalization reduction.

REFERENCES

• 1: Rakesh Agrawal , Tomasz Imieliński , Arun Swami, Mining association rules between sets of items in large databases, Proceedings of the 1993 ACM SIGMOD international conference on Management of data, p.207-216, May 25-28, 1993, Washington, D.C., United States
• 2: T. Berners-Lee, J. Hendler, and O. Lassila. Semantic web. Scientific American, 284(5):35--43, 2001.
• 3: Ramakrishnan Srikant , Rakesh Agrawal, Mining Generalized Association Rules, Proceedings of the 21th International Conference on Very Large Data Bases, p.407-419, September 11-15, 1995
• 4: W3C. W3C RDF Specification.

INDEX TERMS

Primary Classification:
  H. Information Systems
  H.2 DATABASE MANAGEMENT
      H.2.8 Database applications
          Subjects: Data mining

General Terms:
Algorithms

Keywords:
RDF mining, association rule mining