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

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Pubblicato in:The Artificial Intelligence Review vol. 53, no. 6 (Aug 2020), p. 4289
Autore principale: Yu Bengong
Altri autori: Fan Zhaodi
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Springer Nature B.V.
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024 7 |a 10.1007/s10462-019-09793-6  |2 doi 
035 |a 2423976957 
045 2 |b d20200801  |b d20200831 
084 |a 68693  |2 nlm 
100 1 |a Yu Bengong  |u Hefei University of Technology, School of Management, Hefei, China (GRID:grid.256896.6); Ministry of Education, Key Laboratory of Process Optimization and Intelligent Decision-Making, Hefei, China (GRID:grid.256896.6) 
245 1 |a A comprehensive review of conditional random fields: variants, hybrids and applications 
260 |b Springer Nature B.V.  |c Aug 2020 
513 |a Journal Article 
520 3 |a 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. 
653 |a Computer vision 
653 |a Machine learning 
653 |a Artificial intelligence 
653 |a Natural language processing 
653 |a Conditional random fields 
653 |a Variants 
653 |a Application 
653 |a Biomedicine 
653 |a Internet 
653 |a Models 
700 1 |a Fan Zhaodi  |u Hefei University of Technology, School of Management, Hefei, China (GRID:grid.256896.6) 
773 0 |t The Artificial Intelligence Review  |g vol. 53, no. 6 (Aug 2020), p. 4289 
786 0 |d ProQuest  |t ABI/INFORM Global 
856 4 1 |3 Citation/Abstract  |u https://www.proquest.com/docview/2423976957/abstract/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch 
856 4 0 |3 Full Text - PDF  |u https://www.proquest.com/docview/2423976957/fulltextPDF/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch