AN AUTOMATED GRADING MODEL COMBINED IMPROVED LSA WITH PLAS

摘要：

This paper proposes improvements for the method of Latent Semantic Analysis (LSA).The method is used to grade the English text automatically.But, there are still many deficiencies to be improved.Firstly, one important factor that affects the quality of LSA is the weighting method to the term-document matrix.The weighted function directly influence the results of the final score which calculated by the computer. Secondly, Probabilistic Latent Semantic Analysis (PLSA) is also applied to the automated grading model (AGM).In contrast to standard LSA by Singular Value Decomposition, the probabilistic variant has a solid statistical foundation and defines a proper generative data model.The experiments indicate that the result of the improved model has proven to be more precise.

关键词： Latent Semantic Analysis Weighted Function Probabilistic Latent Semantic Analysis Automated Grading Model

作者: GUIMIN HUANG GUOYUAN CAO YA ZHOU

作者单位: Guilin University of Electronic Technology Guilin 541004,China

会议类型: 国际会议

会议名称: 2011 3rd International Conference on Computer Technology and Development(2011第三届计算机技术与发展国际会议 ICCTD2011)

会议地点: 成都

会议语种:英文

页码: 872-876

在线出版日期: 2011-11-25（万方平台首次上网日期，不代表论文的发表时间）