Semi-supervised learning of the hidden vector state model for extracting protein–protein interactions
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摘要
ObjectiveThe hidden vector state (HVS) model is an extension of the basic discrete Markov model in which context is encoded as a stack-oriented state vector. It has been applied successfully for protein–protein interactions extraction. However, the HVS model, being a statistically based approach, requires large-scale annotated corpora in order to reliably estimate model parameters. This is normally difficult to obtain in practical applications.
论文关键词：Semi-supervised learning,Hidden vector state model,Protein–protein interactions,Information extraction
论文评审过程：Received 15 December 2006, Revised 18 June 2007, Accepted 6 July 2007, Available online 17 August 2007.
论文官网地址：https://doi.org/10.1016/j.artmed.2007.07.004
