博碩士論文 etd-0708114-101901 詳細資訊


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姓名 陳韋亭(Wei-ting Chen) 電子郵件信箱 E-mail 資料不公開
畢業系所 資訊管理學系研究所(Information Management)
畢業學位 碩士(Master) 畢業時期 102學年第2學期
論文名稱(中) 大腦決策機制之資料探勘研究
論文名稱(英) Decision Mechanisms of Human Brain: A Data mining Approach
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    紙本論文:2 年後公開 (2016-08-08 公開)

    電子論文:使用者自訂權限:校內 2 年後、校外 2 年後公開

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    統計 本論文已被瀏覽 5396 次,被下載 910 次
    摘要(中) 決策是人類適應環境的一種行為,存在於我們的生活中,從簡單的賭博決策到相對複雜的投資決策,決策行為在人們的生活中日益重要。而近年來有越來越多研究大腦決策的相關文獻,也累積了許多對大腦決策機制的了解,但是由於大腦的複雜性,有些研究的結果可能不盡然相同,甚至相互矛盾,導致後續學者在進行相關研究時候的困擾,因而無法建立正確的腦區與決策任務的關係連結。
    因此,本研究的目的在建構一個資料探勘的系統,將目前現有的大腦決策相關文獻進行彙整,並利用多層次關聯分析來找尋腦區資料與決策任務之間的關聯規則,包括風險,模糊,獎賞,信任等多項決策的任務。本研究先找出100篇已發表文獻中事件以及腦區的關係,並加以編碼,將相關資料建置成系統網站,以驗證所提出方法的可行性。
    摘要(英) Decision making is a human activity that we perform all the time, from a simple game to a complex stock investment. It is the most important activity in human life. Recently, researchers have applied neuroscience methods to investigate how human brains make decisions. The research area is called decision neuroscience. Due to the complexity of the brain, however, research findings reported in literature are often inconsistent. Although the findings may be useful in some sense, inconsistent findings often lead to confusion. The inconclusive findings also make the research stream controversial, which indicates a need for aggregation.
      One way to derive more informative conclusion from inconsistent findings is to conduct a meta-analysis on existing literature. In order to fill the gap, therefore, this study applies the technique of multi-level association rules to develop a data mining system for identifying brain association with different decision tasks, including risk, ambiguity, trust, rewards, and so on. We used published literature in neurodecision making to code our raw data and use the multi-level association rule technique to find the association between tasks and functional areas in human brain. A website for this purpose has been built and 100 coded articles are used to evaluate the identified brain associations. This system can help users better understand the relationship between brain areas and different decision tasks.
    關鍵字(中)
  • 多層次關聯分析
  • 決策神經科學
  • 認知神經科學
  • 大腦決策
  • 彙總分析
  • 關鍵字(英)
  • Meta-Analysis
  • multi-level association rules
  • Cognitive neuroscience
  • decision neuroscience
  • Brain decision making
  • 論文目次 論文審定書 i
    誌謝 ii
    中文摘要 iii
    英文摘要 iv
    目次 v
    圖次 vii
    表次 viii
    第一章緒論 1
    第一節 研究背景 1
    第二節 研究動機 2
    第三節 研究目的與問題 3
    第四節 研究流程與論文結構 3
    第二章 文獻探討 5
    第一節 決策神經科學的研究問題 5
    第一項 風險 (Risk) 7
    第二項 模糊 (Ambiguity) 8
    第三項 喜好(Preference) 8
    第四項 獎賞(Rewards) 9
    第五項 信任(Trust) 10
    第六項 選擇 (Choice) 13
    第七項 情緒 (Emotion) 14
    第二節 資料探勘(Data Mining)技術之發展 15
    第一項 資料探勘技術之發展 15
    第二項 資料探勘的流程 16
    第三項 關聯規則 17
    第四項 多層次關聯規則 18
    第五項 資料探勘的應用 22
    第三章研究方法 23
    第一節 設計科學研究法 23
    第二節 系統雛型之架構 24
    第四章 系統分析設計與建置 26
    第一節 系統需求分析 26
    第一項 系統功能分析 26
    第二項 系統開發環境分析 27
    第二節 系統功能與介面設計 28
    第一項多層次關聯分析之功能 28
    第二項 網站介面之功能 37
    第三項系統展示-查詢腦區與事件之規則 41
    第五章 系統驗證 42
    第一節 事件與腦區的關聯 42
    第二節 腦區與事件的關聯 43
    第三節 腦區與腦區間的關聯 45
    第六章 結論與建議 46
    第一節 研究結論 46
    第二節 研究貢獻 47
    第三節 研究限制與未來展望 47
    參考文獻 48
    附錄一 GID編碼 61
    附錄二 編碼後的資料 64
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    口試委員
  • 黃三益 - 召集委員
  • 陳灯能 - 委員
  • 梁定澎 - 指導教授
  • 口試日期 2014-07-24 繳交日期 2014-08-08

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