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SOFTWARE
2002

Temporal Probabilistic Concepts from Heterogeneous Data Sequences

10 years 26 days ago
Temporal Probabilistic Concepts from Heterogeneous Data Sequences
We consider the problem of characterisation of sequences of heterogeneous symbolic data that arise from a common underlying temporal pattern. The data, which are subject to imprecision and uncertainty, are heterogeneous with respect to classification schemes, where the class values differ between sequences. However, because the sequences relate to the same underlying concept, the mappings between values, which are not known ab initio, may be learned. Such mappings relate local ontologies, in the form of classification schemes, to a global ontology (the underlying pattern). On the basis of these mappings we use maximum likelihood techniques to handle uncertainty in the data and learn local probabilistic concepts represented by individual temporal instances of the sequences. These local concepts are then combined, thus enabling us to learn the overall temporal probabilistic concept that describes the underlying pattern. Such an approach provides an intuitive way of describing the tempora...
Sally I. McClean, Bryan W. Scotney, Fiona Palmer
Added 23 Dec 2010
Updated 23 Dec 2010
Type Journal
Year 2002
Where SOFTWARE
Authors Sally I. McClean, Bryan W. Scotney, Fiona Palmer
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