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A comprehensive review of conditional random fields: variants, hybrids and applications

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Publicado en:The Artificial Intelligence Review vol. 53, no. 6 (Aug 2020), p. 4289
Publicado:
Springer Nature B.V.
Materias:
Computer vision
Artificial intelligence
Machine learning
Conditional random fields
Natural language processing
Probability
Random variables
Probability distribution
Entropy
Variants
Application
Biomedicine
Internet
Models
Acceso en línea:Citation/Abstract
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Resumen:The conditional random fields (CRFs) model plays an important role in the machine learning field. Driven by the development of the artificial intelligence, the CRF models have enjoyed great advancement. To analyze the recent development of the CRFs, this paper presents a comprehensive review of different versions of the CRF models and their applications. On the basis of elaborating on the background and definition of the CRFs, it analyzes three basic problems faced by the CRF models and reviews their latest improvements. Based on that, it presents the applications of the CRFs in the natural language processing, computer vision, biomedicine, Internet intelligence and other relevant fields. At last, specific analysis and future directions of the CRFs are discussed.
ISSN:0269-2821
1573-7462
DOI:10.1007/s10462-019-09793-6
Fuente:ABI/INFORM Global