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2018 | OriginalPaper | Buchkapitel

Algorithms of Sequential Pattern Generation with Noise using Stochastic and Fuzzy Models

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Abstract

A task of sequential pattern generation can be considered as a problem which is inverse to sequential pattern mining. This paper presents two novel approaches to the sequential pattern generation with noise, namely the approach based on stochastic automata and context-free grammars and the approach based on Hidden Markov model. The distinctive feature of these methods is the suitability to produce an output in the noisy and fuzzy input data. Also, we present the detailed calculation algorithms to the proposed approaches.

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Metadaten
Titel
Algorithms of Sequential Pattern Generation with Noise using Stochastic and Fuzzy Models
verfasst von
Maria A. Butakova
Andrey V. Chernov
Alexander N. Guda
Copyright-Jahr
2018
DOI
https://doi.org/10.1007/978-3-319-68321-8_21