基于文本特征和奇异值分解的印尼语流行文章的自动文本摘要

2015 International Seminar on Intelligent Technology and Its Applications (ISITIA) Pub Date : 2015-05-20 DOI:10.1109/ISITIA.2015.7219948

F. Gunawan, Adrian Victor Juandi, B. Soewito

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引用次数: 4

摘要

随着大量流行文章的存在，机器文本摘要是必要的。本文对印尼语流行文章的潜在语义分析技术进行了评价。摘要的性能是根据精度、召回率和f值来评估的。结果，性能似乎相当高，特别是当总结水平为50%时。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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An automatic text summarization using text features and singular value decomposition for popular articles in Indonesia language

The machine text summarization is of necessary with the existing of the enormous amount of popular articles. This work evaluates the latent semantic analysis technique to summarize popular articles in Indonesia language. The summarization performance are evaluated with respect to precision, recall, and F-measure. As results, the performance seems to be reasonably high particularly when the summarization level is 50%.

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来源期刊

2015 International Seminar on Intelligent Technology and Its Applications (ISITIA)

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