文章基本信息

标题：Automatic Text Summarization Using Latent Drichlet Allocation (LDA) for Document Clustering
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作者：Erwin Yudi Hidayat ; Fahri Firdausillah ; Khafiizh Hastuti 等
期刊名称：IJAIN (International Journal of Advances in Intelligent Informatics)
印刷版ISSN：2442-6571
电子版ISSN：2548-3161
出版年度：2015
卷号：1
期号：3
页码：132-139
DOI：10.26555/ijain.v1i3.43
语种：English
出版社：Universitas Ahmad Dahlan
摘要：In this paper, we present Latent Drichlet Allocation in automatic text summarization to improve accuracy in document clustering. The experiments involving 398 data set from public blog article obtained by using python scrapy crawler and scraper. Several steps of clustering in this research are preprocessing, automatic document compression using feature method, automatic document compression using LDA, word weighting and clustering algorithm The results show that automatic document summarization with LDA reaches 72% in LDA 40%, compared to traditional k-means method which only reaches 66%.
关键词：LDA; text summarization; clustering; k-means