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    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/137209


    Title: A Decision Support System for Detecting Low-quality Articles in Content Farms
    Authors: 杜雨儒
    Tu, Yu-Ju;Kao,Han Chun
    Contributors: 資管系
    Date: 2020-10
    Issue Date: 2021-09-22 10:19:38 (UTC+8)
    Abstract: Recently, content farms (websites) have drawn considerable attentions as well as critics, because their main business models are focused on supplying low quality articles, rather than high quality ones, to the Internet. In this study, we show that such low quality articles may include fake articles, advertorial articles, and plagiarized articles. Further, we propose a decision support system based on integrating multiple machine learning approaches to detect low-quality articles from content farms.
    Relation: TANET 2020, National Taiwan University
    Data Type: conference
    Appears in Collections:[Department of MIS] Proceedings

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