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研究生:李天祥
研究生(外文):Tan-Sheng Li
論文名稱:以模糊語意塑模法萃取決策知識之研究
論文名稱(外文):A study of linguistic modeling for decision knowledge discovery
指導教授:李昇暾李昇暾引用關係
指導教授(外文):Sheng-Tun Li
學位類別:碩士
校院名稱:國立高雄第一科技大學
系所名稱:資訊管理所
學門:電算機學門
學類:電算機一般學類
論文種類:學術論文
論文出版年:2002
畢業學年度:90
語文別:中文
論文頁數:121
中文關鍵詞:語意塑模知識探勘時間序列知識工程模糊分群模糊塑模財務報表分析知識引取知識管理
外文關鍵詞:knowledge engineeringfuzzy clusteringfinancial report analysisKnowledge managementlinguistic modelingfuzzy modelingtime series
相關次數:
  • 被引用被引用:8
  • 點閱點閱:496
  • 評分評分:
  • 下載下載:134
  • 收藏至我的研究室書目清單書目收藏:2
在快速變遷與動盪的商場環境中,「知識」已被視為公司企業與經濟體保持競爭優勢最具關鍵的資源,而知識管理也因此成為現代管理動中的主要議題,其涵蓋了企業內知識的建立、儲存、分享、以及再使用。然而在過去許多知識勘探的研究中所使用的方法論,仍以建立預測模式為主,而利用精確的數理模型來進行預測模式之建立對於知識的貢獻仍備受質疑,因此本研究即提出一套語意知識探勘法,提供一個改以「知識」為主題的資料探勘模式,以強化知識管理中的隱性知識移轉活動。本研究實際應用兩個案例進行知識法則之探勘,以驗證本研究所提出之方法。

從領域專家中挖掘其內隱知識在當前的知識管理上是一項十分有趣且極具挑戰的重要工作,本研究第一個應用個案即為財務報表分析專家決策過程的知識萃取,應用本研究所提出之模糊語意塑模法將專家決策之內隱知識予以萃取出來,並轉換為人類口語化之法則。實證資料來源將以國內數百家上市上櫃公司的財務報表資料為實驗對象,並商請一位資深會計師協助進行實驗,以驗證本研究所提出的方法能夠有效地將專家內隱知識外顯化,並得以修正及改善其決策知識。

除此之外,知識並非僅只存在於專家的思維中,知識亦存在於過去歷史現象之中,因此本研究的第二個應用案例即針對時間序列資料進行知識法則探勘,以不同之知識來源進行知識發掘的研究。本研究亦應用時間序列的資料處理法,將臺股大盤收盤資訊予以匯整並進行其特徵擷取,以配合模糊語意塑模法之使用。本研究再行配合語意塑模法,將上述所開採之模糊數學模式予以轉換為較廣為人接受的口語知識,以完成自時間序列資料中探勘隱藏於知識的目的。
In the ever-fast dynamically changed business environment, the key of remaining competitive advantage is the knowledge, the core capabilities of the organizational units in the global economic society. Thus knowledge management becomes the major issue of current management activities, which involves creating, innovation, repository, sharing, and re-use of mind’s sprit. There have been a lot of researches prove that IT can support knowledge management tasks, however, most of them are mainly focused on “knowledge prediction” as the research goal. In addition, empirical studies indicated that forecasting tasks are of limited contribution to knowledge management. Hence, to fit the goal for matching the contemporary knowledge society activities, this research propose an hybrid approach of fuzzy modeling and linguistic approximation, in order to enhance the tacit knowledge transfer for decision knowledge of a domain expert. Two empirical cases were conducted in this thesis for demonstrating the feasibility and capability of the hybrid approach.

To elicit the tacit knowledge from domain experts is an exciting and challenging work. Therefore, the first case of this thesis focuses on financial statement knowledge discovery. To reach this goal, we propose an approach of linguistic modeling to transform the traditional fuzzy model into linguistic and human understandable knowledge instead of the mathematical equation in fuzzy model. Hundreds of Taiwan’s companies financial statement report are investigated , the experimental results show that financial decision knowledge extracted from this approach matches three main objectives in this research, which are accuracy, simplicity, and comprehensibility.

The knowledge is not only captured in financial statement decision experts but also persisted in large sequence event databases, such as Taiwan Stock Exchange as in the second empirical case of this thesis. To reach the goal of time series knowledge discovery, this research collects and transforms the original sequences into discrete and window frame-based data set. Furthermore, the data set then is fed into the linguistic model to extract the interesting and hidden financial decision for investors. Those knowledge rules are all compatible with three major objectives in this research.
目錄i
圖目錄iii
表目錄v
壹、 緒論1
一、 研究背景1
二、 研究動機4
三、 研究目的7
四、 研究方法概述10
五、 研究架構11
六、 論文架構12
貳、 文獻探討14
一、 模糊邏輯14
二、 模糊塑模15
三、 模糊分群17
四、 自組織神經網路19
五、 分群效度22
六、 規則投影24
七、 模糊模式化簡24
八、 語意概似估計26
參、 研究設計與方法30
一、 實驗資料簡介30
(一) 財務會計報表分析專家決策資料30
(二) 台灣股票交易時間序列32
二、 財務會計報表分析專家決策資料34
(一) 探勘目的34
(二) 研究流程35
(三) 特徵擷取36
(四) 模糊塑模41
(五) 集群分析43
(六) 分群效度驗證46
(七) 群形投影47
(八) 模糊法則化簡50
(九) 語意塑模54
(十) 交互驗證57
三、 台灣股票交易時間序列58
(一) 探勘目的58
(二) 研究流程59
(三) 移動視窗61
(四) 大盤技術指標分析62
(五) 階層式自組織神經網路64
(六) 分群效度驗證65
(七) 自組織神經網路法則投影66
四、 模擬實驗環境67
肆、 實證分析69
一、 財務會計報表分析專家決策資料69
(一) 實驗一:統計逐步迴歸變數選取及模糊語意塑模法70
(二) 實驗二:非線性迴歸及模糊塑語意模法80
(三) 實驗小結89
二、 台灣股票交易時間序列91
(一) 因變項處理結果92
(二) 模式學習結果96
(三) 實驗小結101
伍、 結論102
一、 研究結論102
二、 研究貢獻103
三、 研究限制106
四、 未來研究方向107
(一) 語意法則匯整107
(二) 語意塑模詞述修訂108
(三) 時間序列特徵擷取109

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