在分形近邻距离的基础上，提出了分形奇异值近邻距离，并把分形编码和局部奇异值分解结合起来，提高了识别率。
Fractal singular value neighbor distance is brought forward based on fractal neighbor distance. Fractal coding and local singular value decomposition are used to improve the recognition rate.
同时为了进一步降低存局部潜在语义分类的存储空间的开销，采用半离散分解方法替代奇异值分解方法。
Meanwhile to reduce the cost of memory space, this paper takes the Semi-Discrete Decomposition Method rather than the Singular Value Decomposition.
同时为了进一步降低存局部潜在语义分类的存储空间的开销，采用半离散分解方法替代奇异值分解方法。
Meanwhile to reduce the cost of memory space, this paper takes the Semi-Discrete Decomposition Method rather than the Singular Value Decomposition.
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