淡江大學機構典藏:Item 987654321/116629
English  |  正體中文  |  简体中文  |  全文筆數/總筆數 : 64191/96979 (66%)
造訪人次 : 8295168      線上人數 : 6693
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library & TKU Library IR team.
搜尋範圍 查詢小技巧:
  • 您可在西文檢索詞彙前後加上"雙引號",以獲取較精準的檢索結果
  • 若欲以作者姓名搜尋,建議至進階搜尋限定作者欄位,可獲得較完整資料
  • 進階搜尋
    請使用永久網址來引用或連結此文件: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/116629


    題名: Extracting New Opinion Elements in the Semi-automatic Chinese Opinion-Mining System from Internet Forums
    作者: Wu, Shih-Jung, et al.
    關鍵詞: Opinion mining system;Sentiment analysis;Customer review
    日期: 2016-07-13
    上傳時間: 2019-05-14 12:10:19 (UTC+8)
    摘要: Articles posted on a forum often contain new Internet terms related to opinion elements. Consequently, existing Chinese opinion-mining systems may exhibit low recall and precision because they cannot recognize these new Internet terms. Therefore, we designed an algorithm to elaborate on the opinion elements of such articles by extracting the new terms. By ignoring any uncommon opinion element that appears only once, we determine whether the new term identified through manual judgment is a useful opinion element for a specific domain and add it to the thesaurus. In comparison with semi-automatic annotation methods, our approach can save considerable labor. The same Chinese word may have different meanings depending on the context, and this fact is prone to cause difficulties by changing the polarity or meaning of certain opinion elements, leading to errors in the analysis results of many Chinese systems. We designed appropriate algorithms to address this problem. Meanwhile, this system extracts the opinion elements from an article based on its established thesaurus and simultaneously considers various sentence patterns, the default topic, and clause priority to determine the opinion tendency of the author.
    DOI: 10.1007/978-981-10-3187-8_51
    顯示於類別:[資訊創新與科技學系] 會議論文

    文件中的檔案:

    檔案 描述 大小格式瀏覽次數
    index.html0KbHTML126檢視/開啟
    index.html0KbHTML210檢視/開啟

    在機構典藏中所有的資料項目都受到原著作權保護.

    TAIR相關文章

    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library & TKU Library IR teams. Copyright ©   - 回饋