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研究生：	蔡岳勳 Tsai, Yue-Shiun
論文名稱：	使用概念擴展之學習物件辭書查詢－以JLOO 為例 Learning Object Querying with Ontology Concept Expansion － Case Study Using JLOO
指導教授：	王宗一 Wang, Tzong-I
學位類別：	碩士 Master
系所名稱：	工學院 - 工程科學系 Department of Engineering Science
論文出版年：	2006
畢業學年度：	94
語文別：	中文
論文頁數：	62
中文關鍵詞：	學習物件、辭書、概念擴展
外文關鍵詞：	Learning Object, Concept Expansion, Ontology
相關次數：	點閱：68 下載：2
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　　近年來網路發展迅速，網路上可取得的資源與日俱增，但這些過多的資源反而造成使用者的負擔，雖然搜尋引擎方便且易上手，但要過濾並取得所需要的資訊仍需花費一番功夫。然而對於想利用網路資源的初學者，光是選擇下一個適合的學習教材就已經相當不容易了，若查詢取回一大堆不相干的課程，對於學習者更是一大困擾。
　　本論文主要是針對Java初級課程的學習領域，以Java Learning Object Ontology（JLOO）為系統的辭書，做為學習者在此領域的一個引導，利用辭書架構除了取得使用者意向，更以辭書概念式擴展來查詢學習物件，提供最相關的學習物件回應使用者，即便使用者不了解辭書，能可以輕易的取得相關資訊。
　　使用類似傳統關鍵字查詢的tf-idf公式取得基礎概念對於使用者查詢的相關程度，並以基礎概念為基礎，找出對於其語意路徑上所有概念的影響，以便決定一個廣義概念來涵蓋所有（或最多）的基礎概念，用來表示使用者的意向所趨，最後將使用者意向根據系統日誌擴展，配合辭書所管理的學習物件，來取得最符合使用者需求的學習課程。

　　In the past few years, the vigorous development of Internet makes enormous information resources obtainable with a single click. However this huge amount of resources also cause recognition burden on users when trying to grab what they need. Although search engines are convenient in collecting as if relevant documents, they do not help much in identifying desirable ones. People who search still have to spend a lot of time on filtering and choosing information they needed. For a novice learner trying to utilize learning resources from repositories on the network, it is already difficult to figure out how to find suitable teaching materials, let alone facing such lot of irrelevant course objects.
　　This study focuses on developing a methodology for helping learners who are novel to a specific field. The thesis uses java programming language as an example for demonstration. The Java Learning Object Ontology (JLOO) is used as system ontology that has being developed as a guide in this field for the learners. The proposed methodology uses ontology to infer a learner’s intention before using a concept expansion algorithm that, base on the learners’ intention, to include more relevant concepts as the query when retrieving learning objects. The most relevant learning objects could be fetched even when the learners are not familiar with the domain.
　　The concept expansion algorithm uses traditional tf-idf formula to calculate the relevant degree of the basic concepts on an ontology hierarchy, which are matched with keywords of a user query. It then calculates the influence of other concepts on the semantic path of basic concepts. Some user intention trees are establish, from which a most suitable one is selected. The result one is further expanded according to system logs that record the past learning behaviors of the user and other users. Finally, the most relevant learning objects are fetched and recommended to the user.

中文摘要............................................. i
Abstract............................................. ii
致謝................................................. iii
目錄................................................. iv
圖目錄............................................... vii
表目錄............................................... x
第一章 緒論.......................................... 1
1 研究背景......................................... 1
2 研究動機......................................... 2
3 研究目的......................................... 2
4 章節介紹......................................... 3
第二章 相關研究回顧.................................. 4
1 語意網........................................... 4
2 辭書............................................. 6
3 辭書描述語言..................................... 7
3.1 可延伸標籤語言................................. 7
3.2 基於可延伸標籤語言所發展的語意語言............. 8
3.2.1 RDF ......................................... 9
3.2.2 RDFS ........................................ 10
3.2.3 DAMIL+OIL ................................... 10
3.2.4 OWL.......................................... 11
4 辭書描述語言編輯器Protege........................ 12
5 學習物件......................................... 13
第三章 系統辭書建構.................................. 16
1 辭書建構方法..................................... 16
2 辭書建構......................................... 17
2.1 確立JLOO 的領域範圍與應用目的.................. 17
2.2 考量現有可利用的辭書........................... 18
2.3 列出JAVA 程式語言的關鍵術語.................... 18
2.4 定義類別與其階層............................... 19
2.5 定義類別的屬性................................. 24
2.6 建立實例....................................... 26
第四章 辭書概念擴展查詢.............................. 27
1 辭書擴展架構設計考量............................. 27
2 辭書概念擴展查詢概念圖........................... 29
3 辭書概念擴展查詢................................. 30
3.1 使用者意向萃取流程............................. 30
3.1.1 使用者查詢................................... 30
3.1.2 分析查詢關鍵字與辭書概念關鍵字............... 31
3.1.3 對應關鍵字的相關概念......................... 31
3.1.4 產生候選使用者意向樹......................... 33
3.1.5 移除語意混淆................................. 34
3.1.6 使用者意向萃取實例........................... 35
3.2 概念擴展流程................................... 40
3.2.1 相關概念擴展................................. 40
3.2.2 計算學習物件與使用者意向的相關程度........... 44
第五章 系統實作...................................... 45
1 系統模組......................................... 45
2 Jena Semantic Web Framework ..................... 47
3 系統功能......................................... 48
4 系統之效能評估................................... 55
第六章結論與未來展望................................. 60
1 結論............................................. 60
2 未來展望......................................... 62
參考文獻............................................. 63
自述................................................. 66
                                    

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校內：2007-08-22公開
校外：2007-08-22公開

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