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研究生： 陳乾元
Chen, Chien-Yuan
論文名稱： 啟發式階層式知識結構建置之研究
Heuristic-based Approach for Constructing Hierarchical Knowledge Structure
指導教授： 李昇暾
Li, Sheng-Tun
學位類別： 碩士
Master
系所名稱： 管理學院 - 資訊管理研究所
Institute of Information Management
論文出版年： 2008
畢業學年度： 96
語文別： 英文
論文頁數： 48
中文關鍵詞： 樹狀知識結構 、本體論 、概念階層 、知識擷取 、概念模型
外文關鍵詞： tree-based hierarchical knowledge structure, concept hierarchy, ontology, conceptual model, knowledge socialization
相關次數： 點閱：133  下載：2 
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    • 知識經濟的世代，知識管理是每個企業核心競爭力的關鍵。知識可以視為是一群互相關聯的概念，普遍存在文獻或是領域專家的心智中。將知識外顯化是知識管理的首要步驟，但最耗費人力與時間的，莫過於如何將擷取出來的知識，做適當的表達。知識的表達有許多方法，樹狀階層的知識結構是長久以來所慣用的知識表達結構，它可以很直覺地將知識整體地展現出來，並傳達明確的階層觀念。許多相關的研究皆致力於(半)自動化的階層結構建置，本研究提出一個新穎的演算法，以概念之間的相似度為基礎，(半)自動化建構概念間的樹狀階層結構。進一步，我們討論數個根節點的特性用以推薦根節點。概念間樹狀階層結構的產生，亦可應用於語意網，做為建構本體論的第一步。

    Being in the times of knowledge economy, knowledge is the core of competence of every enterprise. Knowledge can be regarded as a set of mutual associated concepts which generally exists in corpora or experts’ cognitions. Knowledge socialization is the first step of Knowledge Management (KM) and the most laborious of it is to appropriately express the socialized knowledge. Lots of formats can be used to express knowledge, the most common being the tree-based hierarchical knowledge structure. It can express the knowledge holistically and render explicit hierarchy sense. Many researches propose (semi-)automatic hierarchical knowledge structure constructing approaches. We present a novel methodology to construct tree-hierarchy (semi-)automatically based on similarities between concepts. Further, several characters of the root are discussed for root recommendation. The resulting structure can be the initial step of building ontology.

    Chapter 1 Introduction 1 1.1 Motivation and background 1 1.2 Objectives 2 1.3 Assumptions 4 1.4 Research procedure 4 Chapter 2 Literature Review 6 2.1 Lattice-based hierarchical knowledge structure 6 2.2 Tree-based knowledge structure 9 2.3 The characters of the root 14 2.4 Brief summary 15 Chapter 3 Methodology 18 3.1 Corpus knowledge socialization 20 3.1.1 Preprocess 20 3.1.2 Vector Space Model (VSM) 20 3.1.3 Cosine measure 21 3.2 The hierarchy feature 22 3.3 Heuristic Tree-hierarchy Construction Algorithm (HTCA) 24 3.3.1 Main 24 3.3.2 HTCA 25 3.4 The characters of a root 29 3.5 Evaluation module 31 3.5.1 Root recommendation evaluation 31 3.5.2 Tree-hierarchy structure evaluation 31 Chapter 4 Implementation and Experiments 33 4.1 Implementation 33 4.2 Data collection 33 4.3 Experiments and results of root recommendation 35 4.4 Experiments and results of tree-hierarchy structure 37 4.4.1 Initial results 37 4.4.2 Similarity adjustment 38 4.4.3 Similarity adjustment results 39 Chapter 5 Conclusions and future works 42 References 45 Appendix A. The golden standard of musical instrument 48

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