Enhanced sparse representation classifier for text classification
作者：
Highlights：
• Empirical demonstration of Sparse classification methods on text data.
• Minimum residual error and class wise dictionaries based methods are most efficient.
• Proposed a dynamic dictionary refinement algorithm.
• Proposed work improves computational speed and classification performance.
• Dictionary refinement procedure addressed the problem of over-reliance on training data.
摘要
•Empirical demonstration of Sparse classification methods on text data.•Minimum residual error and class wise dictionaries based methods are most efficient.•Proposed a dynamic dictionary refinement algorithm.•Proposed work improves computational speed and classification performance.•Dictionary refinement procedure addressed the problem of over-reliance on training data.
论文关键词：Text classification,Sparse representation,Orthogonal matching pursuit,Dictionary
论文评审过程：Received 22 July 2018, Revised 2 April 2019, Accepted 2 April 2019, Available online 3 April 2019, Version of Record 13 April 2019.
论文官网地址：https://doi.org/10.1016/j.eswa.2019.04.003
