Generalizing Graphs Using Amalgamation and Selection

  • Authors:
  • John G. Stell;Michael F. Worboys

  • Affiliations:
  • -;-

  • Venue:
  • SSD '99 Proceedings of the 6th International Symposium on Advances in Spatial Databases
  • Year:
  • 1999

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Abstract

This work is a contribution to the developing literature on multi-resolution data models. It considers operations for model-oriented generalization in the case where the underlying data is structured as a graph. The paper presents a new approach in that a distinction is made between generalizations that amalgamate data objects and those that select data objects. We show that these two types of generalization are conceptually distinct, and provide a formal framework in which both can be understood. Generalizations that are combinations of amalgamation and selection are termed simplifications, and the paper provides a formal framework in which simplifications can be computed (for example, as compositions of other simplifications). A detailed case study is presented to illustrate the techniques developed, and directions for further work are discussed.