Symbolic state transducers and recurrent neural preference machines for text mining

DOI10.1016/S0888-613X(02)00085-3zbMath1026.68106OpenAlexW2126192466WikidataQ57718524 ScholiaQ57718524MaRDI QIDQ1394984

Christo Panchev, Stefan Wermter, Garen Arevian

Publication date: 25 June 2003

Published in: International Journal of Approximate Reasoning (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/s0888-613x(02)00085-3

zbMATH Keywords

hybrid systemsrecurrent neural networkstext classificationfinite state automatasymbolic transducerspreference Moore Machines

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Natural language processing (68T50)

Cites Work

• WEBSOM -- Self-organizing maps of document collections
• Learning to construct knowledge bases from the World Wide Web
• Towards adaptive Web sites: Conceptual framework and case study
• Constructing deterministic finite-state automata in recurrent neural networks
• NEURAL FUZZY PREFERENCE INTEGRATION USING NEURAL PREFERENCE MOORE MACHINES
• Unnamed Item

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