An Algebraic Method for Compressing Very Large Symbolic Data Tables

Yannis Tzitzikas

Research output: Contribution in Book/Catalog/Report/Conference proceedingConference contribution

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Abstract

Although symbolic data tables summarize huge sets of data they can still become very large in size. This paper proposes a method for compressing a symbolic data table using the recently emerged Compound Term Composition Algebra. One charisma of CTCA is that the closed world hypotheses of its operations can lead to a remarkably high 'compression ratio'. The compacted form apart from having much lower storage space requirements, it allows designing more e±cient algorithms for symbolic data analysis.
Original languageEnglish
Title of host publicationProceedings of the Workshop on Symbolic and Spatial Data Analysis (SSDA) of ECML/PKDD 2004
Publication statusPublished - 2004

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