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A Multidimensional Aggregation Object (MAO) Framework for Computing Distributive Aggregations

  • Meng-Feng Tsai
  • Wesley Chu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2737)

Abstract

Multidimensional aggregation plays an important role in decisionmaking systems. A conceptual Multidimensional Aggregation Object (MAO), which consists of measures, scopes and aggregation function, is introduced to represent relationships among aggregators on addressable subsets of data. In the MAO model, aggregations of low-level (intermediate) data can be reused for aggregations on high-level data along the same dimension. Experimental results show that caching intermediate aggregated data can significantly improve performance. Incremental compensating and full recomputing cache-updating approaches are proposed. Execution plans for deriving the aggregations from MAOs are presented. The proposed data aggregation technique can be applied to data-warehousing, OLAP, and data mining tasks.

Keywords

Data Mining Aggregate Data Data Aggregation Aggregation Function Execution Plan 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Meng-Feng Tsai
    • 1
  • Wesley Chu
    • 1
  1. 1.Computer Science DeptartmentUniversity of CaliforniaLos AngelesUSA

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