基于潜在语义分析的印尼语自动简答评分系统K-Means答案分类方法

A. A. P. Ratna, Naiza Astri Wulandari, Aaliyah Kaltsum, Ihsan Ibrahim, Prima Dewi Purnamasari
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引用次数: 2

摘要

使用K-Means和Latent Semantic Analysis (LSA)方法对印尼语短答案进行自动评分(Simple-O)。在本实验中,使用术语频率-逆文档频率(TF-IDF)提取文本文档特征,然后使用K-Means进行分类。从这个实验中,149个文档被分成5类。使用K-Means聚类的结果与使用human rater聚类的结果匹配度为100%。LSA的评分结果为74%。
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Answer Categorization Method Using K-Means for Indonesian Language Automatic Short Answer Grading System Based on Latent Semantic Analysis
The Automatic Short Answer Grading (Simple-O) has been created for grading short answer with Bahasa Indonesia using K-Means and Latent Semantic Analysis (LSA) method. In this experiment, the text document feature will be extracted using Term Frequency-Inverse Document Frequency (TF-IDF) and then classified using K-Means. From the experiment, 149 documents are expected to be clustered into five classes. The result of the clustering using K-Means is 100% matched with clustering using human rater. The result of grading with LSA is 74%.
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