@inproceedings{93114368bee8467791b3e013a2fd301a,
title = "News topics categorization using latent Dirichlet allocation and sparse representation classifier",
abstract = "Recently, subscribing news from websites has become a new trend for many Internet users. In a news reading browser, it is essential all the news documents are properly categorized. For automatically categorizing the news topics, this paper presents a news categorization method using latent Dirichlet allocation (LDA) and sparse representation classifier (SRC). In our work, the LDA is used as the feature learning method. The multinomial distribution of the news topics is regarded as the feature of the document. These features are stacked as an over-complete dictionary, permitting us to perform SRC-based categorization. The experimental results show that the proposed method outperforms the traditional method.",
keywords = "Computer science, Dictionaries, Resource management, Support vector machines, Testing, Training data, Vocabulary",
author = "Lee, {Yuan Shan} and Rocky Lo and Chen, {Chia Yen} and Lin, {Po Chuan} and Wang, {Jia Ching}",
note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; 2nd IEEE International Conference on Consumer Electronics - Taiwan, ICCE-TW 2015 ; Conference date: 06-06-2015 Through 08-06-2015",
year = "2015",
month = aug,
day = "20",
doi = "10.1109/ICCE-TW.2015.7216819",
language = "???core.languages.en_GB???",
series = "2015 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-TW 2015",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "136--137",
booktitle = "2015 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-TW 2015",
}