English  |  正體中文  |  简体中文  |  全文筆數/總筆數 : 56378/90242 (62%)
造訪人次 : 11682675      線上人數 : 44
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: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/108746


    題名: A Study on Machine Learning for Imbalanced Datasets with Answer Validation of Question Answering
    作者: Day, Min-Yuh;Tsai, Cheng-Chia
    關鍵詞: Answer Validation;Imbalanced Datasets;Machine Learning;Question Answering;QA-Lab;Support Vector Machine
    日期: 2016/07/30
    上傳時間: 2016-12-07 02:10:36 (UTC+8)
    出版者: IEEE
    摘要: Question Answering is a system that can process and answer a given question. In recent years, an enormous number of studies have been made on question answering; little is known about the effects of imbalanced datasets with answer validation of question answer system. The objective of this paper is to provide a better understanding of the effects of imbalanced datasets model for answer validation in a real world university entrance exam question answering system. In this paper, we proposed a question answer system and provided a comprehensive analysis of imbalanced datasets and balanced datasets model with Answer Validation of Question Answering system using NTCIR-12 QA-Lab2 Japanese university entrance exams English translation development and test dataset. As a result, our system achieved 90% accuracy with imbalanced datasets machine learning model for the NTCIR-12 QA-Lab2 development datasets.
    關聯: Proceedings of the 2016 IEEE 17th International Conference on Information Reuse and Integration (IEEE IRI 2016)
    顯示於類別:[資訊管理學系暨研究所] 會議論文

    文件中的檔案:

    檔案 大小格式瀏覽次數
    index.html0KbHTML184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