English  |  正體中文  |  简体中文  |  Post-Print筆數 : 27 |  Items with full text/Total items : 113648/144635 (79%)
Visitors : 51573990      Online Users : 949
RC Version 6.0 © 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
    Home ‧ Login ‧ Upload ‧ Help ‧ About ‧ Administer Goto mobile version


    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/110402


    Title: 基於大數據語料自動生成之中文詞彙聯想與實驗常模之比較
    Other Titles: Comparing Chinese word associations based on big data and experimental norms
    Authors: 林淑晏;宋曜廷;陳學志;張雨霖;陳彥丞
    Lin, Shu-Yen;Sung, Yao-Ting;Chen, Hsueh-Chih;Chang, Yu-Lin;Chen, Yen-Cheng
    Contributors: 國立政治大學邁向頂尖大學計畫創新研究團隊
    Date: 2016
    Issue Date: 2017-06-19 17:31:49 (UTC+8)
    Abstract: 本研究旨在比較基於大數據語料所自動生成之中文詞彙聯想（或稱詞彙共現）與基於真人實驗所建構之聯想常模。我們將Pecina（2010）中的57種詞彙共現強度計算法應用於巨量文本中，產生八萬五千多個常見中文詞彙兩兩間的共現強度（或稱聯想強度）。This study aims to compare two types of word association – the lexical collocations automatically generated using very large corpora and the association norms established in human experiments. Using very large text corpora, we computed the lexical association (or also called collocation) strengths between 85,346 Chinese words using the 57 word association measures described in Pecina (2010). Henceforth, we call the word association thus generated as the collocation dictionary. In order to validate the psychological reality of the automatically-generated word association, the Chinese word association norms established by Chen (1999) was used as a benchmark. The Chen word association norms consist of 1,200 stimulus words. In the free association experiment, each stimulus word was presented to 200 college students who were asked to write down the first word they came up with. For each stimulus word, the number of associate tokens is thus 200, but the average number of associate types is 86.
    Relation: 2016創新研究國際學術研討會: 以人為本的在地創新之跨領域與跨界的對話 2016 International conference on innovation studies- human-centered indigenous innovation: trans-disciplinary dialogue
    會議日期:2016.11.12-13
    Data Type: conference
    Appears in Collections:[2016創新研究國際學術研討會] 會議論文

    Files in This Item:

    File Description SizeFormat
    index.html0KbHTML2711View/Open


    All items in 政大典藏 are protected by copyright, with all rights reserved.


    社群 sharing

    著作權政策宣告 Copyright Announcement
    1.本網站之數位內容為國立政治大學所收錄之機構典藏，無償提供學術研究與公眾教育等公益性使用，惟仍請適度，合理使用本網站之內容，以尊重著作權人之權益。商業上之利用，則請先取得著作權人之授權。
    The digital content of this website is part of National Chengchi University Institutional Repository. It provides free access to academic research and public education for non-commercial use. Please utilize it in a proper and reasonable manner and respect the rights of copyright owners. For commercial use, please obtain authorization from the copyright owner in advance.

    2.本網站之製作，已盡力防止侵害著作權人之權益，如仍發現本網站之數位內容有侵害著作權人權益情事者，請權利人通知本網站維護人員(nccur@nccu.edu.tw)，維護人員將立即採取移除該數位著作等補救措施。
    NCCU Institutional Repository is made to protect the interests of copyright owners. If you believe that any material on the website infringes copyright, please contact our staff(nccur@nccu.edu.tw). We will remove the work from the repository and investigate your claim.
    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - Feedback