Li, D.: Knowledge representation and discovery based on linguistic atoms (1998)
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- Abstract
- Describes a new concept of linguistic atoms with 3 digital characteristics: expected value Ex, entropy En, and deviation D. The mathematical description has effectively integrated the fuzziness and randomness of linguistic terms in a unified way. Develops a method of knowledge representation in KDD, which bridges the gap between quantitative and qualitative knowledge. Mapping between quantities and qualities becomes much easier and interchangeable. In order to discover generalised knowledge from a database, uses virtual linguistic terms and cloud transfer for the auto-generation of concept hierarchies to attributes. Predicitve data mining with the cloud model is given for implementation. Illustrates the advantages of this linguistic model in KDD
- Footnote
- Contribution to a special issue of selected papers from the Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD'97), held Singapore, 22-23 Feb 1997
