中大機構典藏-NCU Institutional Repository-提供博碩士論文、考古題、期刊論文、研究計畫等下載:Item 987654321/68758
English  |  正體中文  |  简体中文  |  Items with full text/Total items : 66984/66984 (100%)
Visitors : 22611409      Online Users : 465
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
  • Adv. Search
    HomeLoginUploadHelpAboutAdminister Goto mobile version


    Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/68758


    Title: 應用語句字詞關係於 多文件自動摘要之方法;Applying relevance terms of sentences on multiple documents summarization 指
    Authors: 黃家榛;Huang,Chia-Chen
    Contributors: 資訊管理學系
    Keywords: 多文件摘要;摘錄式摘要;關聯規則
    Date: 2015-07-21
    Issue Date: 2015-09-23 14:24:40 (UTC+8)
    Publisher: 國立中央大學
    Abstract: 在網路的發達的時代,新聞資訊不斷地在網路世界中擴張散播,過多的新聞使我們
    需花費時間閱讀全文才能找到想找的資訊,因此本研究提出一應用語句字詞關係於多文
    件自動摘要之方法,能自動找出文件中的重點做為摘要,如此即可讓讀者節省閱讀全文
    的時間,本研究將文件中每一語句視為一筆交易資料,並使用關聯規則演算法挖掘出頻
    繁項目集,利用頻繁項目集計算產生關聯字詞,最後依照語句所含之關聯字詞,擷取最
    高語句計分之語句產生摘要,提升從多文件擷取最佳語句作為摘要的準確率。本研究使
    用DUC 2004 新聞文件集進行DUC 2004 task2 之實驗,作出665 bytes 之摘要,經過
    ROUGE 評估摘要品質,本研究所提之方法能有改善多文件自動摘要之潛能。;With the quick development of the internet, the news spread worldwide in minutes, the
    presence of too much information make us hard to understand the issue and spend too much
    time on reading the news to get what we want. Therefore, in this research, we aim to produce
    an extract-based summary to provide readers a quick review of the news. In the research, we
    attempt to use association rule to extract the relevance terms of sentences and apply it on
    documents summarization. In the experiments, the results show that applying relevance terms
    of sentences on multiple documents summarization could be effective in improving the
    precision of summarization.
    Appears in Collections:[Graduate Institute of Information Management] Electronic Thesis & Dissertation

    Files in This Item:

    File Description SizeFormat
    index.html0KbHTML218View/Open


    All items in NCUIR are protected by copyright, with all rights reserved.

    社群 sharing

    ::: Copyright National Central University. | 國立中央大學圖書館版權所有 | 收藏本站 | 設為首頁 | 最佳瀏覽畫面: 1024*768 | 建站日期:8-24-2009 :::
    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - Feedback  - 隱私權政策聲明