臺灣博碩士論文加值系統

隨著行動裝置和無線通訊的發展和普及，人們可以「Anyone、Anydevice、Anytime、Anywhere」來存取所需要的資訊和服務，一項挑戰在於使用者對於服務的要求是非常變動和不確定性，情境感知 (Context-Awareness)或許是一個解決方案，情境感知的技術可以透過許多感應器，例如：GPS、RFID、Camera、Monitor來擷取使用者的情境資訊並深層的了解情境，系統利用情境來提供適當的服務給使用者。
本研究試圖去找到一個完善定義的情境模式，此情境模式能表達人與環境間的關聯，因此採用本體論 (Ontology)來描述情境，OWL (Web Ontology Language)是一個本體論描述語言，它藉著支援XML、RDF和EDF Schema來提供更多辭彙以賦予語意，本研究採用OWL為本體論的描述語言。
情境感知的推理引擎必須考慮到情境的變動性，因此，本研究探討專家系統中推理引擎的相關文獻，本研究使用案例式推理(Case-Based Reasoning)來解決此問題。採用案例式推理於情境感知有兩個優點 (1)案例式推理支援變動情境下的推理， (2)案例式推理可以隨著案例的使用次數來自我調整並提升推理的準確度。本研究比較以位置為基的情境感知系統，實驗結果也證明本研究推理機制確實優於以位置為基的情境感知系統。

Following with the development and popularization of mobile devices and wireless communications, people can “anyone, anydevice, anytime and anywhere” catch information and services. A challenge is that the requirement of users for services is very dynamic and uncertain. “Context-Awareness” may be a solution for this problem. Context-Awareness techniques use sensors (for example, GPS, RFID, Camera, Monitor) to capture user context information and further understand context, and the system makes use of context it captures to provide appropriate services to users.
This research attempts to find a well-defined context model. This context model can describe correlation of people and environment. Therefore, it uses ontology to describe the context. OWL (Web Ontology Language) is an ontology language that is supported by XML, RDF, and RDF Schema by providing additionitional vocabularies along with the formal Semantics. In this research, OWL is used to be the ontology language.
The reasoning engine of Context-Awareness must consider the dynamics of context. Therefore, this research surveys the reasoning engines in related references of some expert systems, and uses case-based reasoning (CBR) to solve the problem. Using CBR for reasoning of Context-Awareness has two advantages: (1) CBR supports reasoning in various context, (2) CBR can self-adjust itself following with cases’ usage times to increase its precision of reasoning. This research compares results with location-based Context-Awareness systems. Results of experiments show that the reasoning engine of this research is better than those of location-based Context-Awareness systems.

目錄…… v
表次…… vii
圖次…… viii
第一章 緒論 1
第一節 研究背景 1
第二節 研究動機 3
第四節 研究目的 5
第五節 研究假設 7
第六節 研究程序 7
第二章 文獻探討 9
第一節 情境感知 (Context-Awareness) 9
第二節 情境本體論 (Context Ontology) 13
第三節 推理引擎 (Reasoning Engine) 21
第三章 研究方法 29
第一節 網路架構和系統架構 29
第三節 實驗步驟 44
第四章 系統建置與驗證 49
第一節 建置情境本體論和案例知識庫 50
第二節 建置推理引擎 63
第三節 實驗設計和系統驗證 66
第五章 結論 85
第一節 研究結果 85
第二節 研究貢獻 86
第三節 未來研究方向 89
參考文獻 91
一、中文文獻 91
二、英文文獻 93
三、網路資料 98
附錄一、案例的資料 99
附錄二、案例的預設權重 109

一、中文文獻

1.江孟峰，案例式知識表示法及轉換法之研究，交通大學資科研究所博士學位論文，1999。
2.陳昌盛，智慧型DNS整合管理系統的設計與實作，交通大學資科研究所博士學位論文，2002。
3.江孟峰、曾憲雄，黃國楨，蔡昌均、林耀聰，專家系統導論工具應用，文魁，2003。
4.張慧羚，應用本體論網路分析於資訊推薦之研究，輔仁大學資管研究所碩士學位論文，2005。
5.潘柏延，知識本體為基建立學習型專家系統之研究-以企業網路問題診斷為例，輔仁大學資管研究所碩士學位論文，2005。
6.許正欣，語意網上自動化建構本體論之研究，輔仁大學資管研究所碩士學位論文，2004。
7.葉美伶，無線點對點之適境化雙贏協商機制，輔仁大學資管研究所碩士學位論文，2004。
8.曹幼文，適地化與適性化之行動廣告資訊推薦機制，輔仁大學資管研究所碩士學位論文，2002。
9.關銘，以OWL DL 及SWRL 為基礎建置推論雛形系統- 以大學排課問題為例，中原大學資訊管理學系碩士學位論文，2004。
10.曾信誠，以本體論為基礎之使用者喜好萃取、隱私權控管與側寫建構，東華大學資訊工程學系碩士學位論文，2004。
11.王惠嘉，以本體論為基礎的可重用軟體元件搜尋方法之研究，成功大學資訊管理學系碩士學位論文，2003。
12.胡訓誠，應用本體論設計ISO文件管理資訊系統，高雄第一科技大學資訊管理學系碩士學位論文，2003。
13.鄭寶庭，使用語意認知機制建置資源調配管理系統之研究，中原大學資訊管理學系碩士學位論文，2004。
14.詹金淩，整合螞蟻理論與案例式推理於知識管理之應用，生產系統工程與管理研究所碩士學位論文，2003。
15.林孟郁，建構一個整合案例式推理和知識圖的模式於專家系統內以診斷個人電腦問題，彰化師範大學資訊管理學系碩士學位論文，2002。
16.林士傑，設計一個以網際網路為基礎之智慧型維修系統，國立交通大學資訊管理學系碩士學位論文，2003。
17.蔡昌均，電腦輔助教學專家系統中知識管理之研究，交通大學資訊科學謝博士學位論文，2002。
18.林仁貴，以RDF規範為基礎之知識文件內容與結構解析技術，清華大學工業工程與工程管理學系碩士學位論文，2004。
19.柯文周，建構以專家系統之推論引擎為基之工作流程管理系統，清華大學工業工程與工程管理學系碩士學位論文，2004。
20.楊智斌、葉坤源，以案例式推理技術輔助專案管理招標文件中廠商資格條件之設定，第七屆人工智慧與應用研討會論文集，2002，頁167-171。

二、英文文獻

1.Aamodt A., Plaza E., Case-Based Reasoning: Foundational Issues, Methodological Variations, and System Approaches, Artificial Intelligence Communications, Vol. 7, No. 1, 1994, pp. 39-59.
2.Bouvin N. O., Christensen B. G., Gronbæk K. & Hansen F. A., HyCon: A Framework for Context-aware Mobile Hypermedia, In The New Review of Hypermedia and Multimedia (NRHM), Vol. 9 No. 1, 2003, pp. 59-88.
3.Chen G. & Kotz D., “A Survey of Context-Aware Mobile Computing Research”, Dartmouth Computer Science Technical Report, Dartmouth College, 2000.
4.Chen H., Finin T. & Joshi A., An Ontology for Context-Aware Pervasive Computing Environments, Workshop on Ontologies and Distributed Systems, Vol. 18, No. 3, 2003, pp. 197-207.
5.Conlan O., Power R., Barrett K., Higel S. & O'Sullivan D., Next Generation Context Aware Adaptive Services, Proceedings of the 1st international symposium on Information and communication technologies, Dublin, Ireland, 2003, pp. 205-212.
6.Carroll J. J., Dickinson I., Dollin C., Reynolds D., Seaborne A. & Wilkinson K., Jena: Implementing the Semantics Web Recommendations, Proceedings of the 13th International World Wide Web Conference, New York, 2004, pp. 74-83.
7.Dey A. K., Understanding and Using Context, Personal and Ubiquitous Computing, Vol.5, No.1, London, UK, 2001, pp. 4-7.
8.Davidyuk O., Riekki J., Rautio V. & Sun J., Context-Aware Middleware for Mobile Multimedia Applications, Proceedings of the 3rd international conference on Mobile and ubiquitous multimedia, Vol. 83, College Park, Maryland, 2004, pp. 213-220.
9.Greiner R., Darken C. & Santoso N. I., Efficient Reasoning, ACM Computing Surveys, Vol. 33, No. 1, New York, 2001, pp. 1-30.
10.Goker A., Watt S., Myrhaug H. I., Whitehead N., Yakici M., Bierig R., Nuti S. K. & Cumming H., An Ambient, Personalised, and Context-Sensitive Information System for Mobile Users, Proceedings of the 2nd European Union symposium on Ambient intelligence, Eindhoven, Netherlands, 2004, pp. 19-24.
11.Gu T., Pung H. K. & Zhang D. Q., Toward an OSGi-Based Infrastructure for Context-Aware Applications, IEEE Pervasive Computing, Vol. 3, No. 4, 2004, pp. 66-74.
12.Guarino N., Formal Ontology and Information Systems, Int'l Conf. on Formal Ontology in Information Systems, Trento, Italy, 1998.
13.Juan J. B. T., Pedro A. González C., Belén D. A., JColibri: An Object-Oriented Framework for Building CBR Systems, Proceedings of the 7th European Conference on Case Based Reasoning, 2004, pp. 32-46.
14.Kolodner J., Case-Based Reasoning, Morgan Kaufmann Publishers, San Mateo, CA, 1993.
15.Koch M., Global Identity Management to Boost Personalization, Proceedings of 9th Research Symposium on Emerging Electronic Marketsl, Basel, 2002, pp. 137-147.
16.Lars B. N., Post Disney experience paradigm? Some implications for the development of content to mobile tourist services, Proceedings of the 6th international conference on Electronic commerce, Delft, The Netherlands, 2004, pp. 657-666.
17.Lewis N., From Customization to Ubiquitous Personalization: Digital Identity and Ambient: Network Intelligence, interactions Vol. 11, No. 2, 2004, pp. 48-50.
18.Middleton S. E., Roure C. D. C. & Shadbolt N. R., Capturing knowledge of User Preferences: Ontologies in Recommender Systems, Proceedings of the 1st international conference on Knowledge capturea, Victoria, British Columbia, Canada, 2001, pp. 100-107.
19.Middleton S. E., Shadbolt N. R. & Roure D. D., Ontological User Profiling in Recommender Systems, ACM Transactions on Information Systems, Vol. 22, No. 1, 2004, pp. 54-88.
20.Middleton S. E., Shadbolt N. R. & Roure D. D., Capturing interest through inference and visualization: ontological user profiling in recommender systems, Proceedings of the 2nd international conference on Knowledge capture, Sanibel Island, USA, 2003, pp. 62-69.
21.Natalya F. N. & Deborah L. M., Ontology Development 101: A Guide to Creating Your First Ontology. Stanford Knowledge Systems Laboratory Technical Report KSL-01-05, 2001.
22.Rector A., Modularisation of domain ontologies implemented in description logics and related formalisms including OWL, Proceedings of the 2nd international conference on Knowledge capture, Sanibel Island, USA, 2003, pp. 121-128.
23.Studer R., Benjamins V. R. & Fensel D., Knowledge Engineering: Principles and Methods, Data and Knowledge Engineering, Vol. 25, No. 1-2, pp. 161-197.
24.Schilit B. N. & Theimer M. M., Disseminating Active Map Information to Mobile Hosts, IEEE Network Vol.8 No.5, 1994, pp. 22-32.
25.Schilit B., Adams N. & Want R., Context-Aware Computing Applications, Proceedings of the Workshop on Mobile Computing Systems and Applications, Santa Cruz, USA, 1994, pp. 85-90.
26.SchulzS., CBR-Works a state-of-the-art shell for case-based application building, Proceedings of the German Workshop on Case-Based Reasoning, Wrzburg, Germany, 1999.
27.Schuurmans J. & Zijlstra E., Towards a continuous personalization experience, Proceedings of the Eighth Conference on Dutch Directions in HCI (SIGCHI.NL), Amsterdam, Holland, 2004, pp. 19-22.
28.Tung H. W. & Soo V. W., A Personalized Restaurant Recommender Agent for Mobile E-Service, Proceedings of the 2004 IEEE International Conference on e-Technology, e-Commerce and e-Service, Taipei, Taiwan, 2004, pp. 259-262.
29.Weibenberg N., Voisard A. & Gartmann R., Using Ontologies in Personalized Mobile Applications, Proceedings of the 12th annual ACM international workshop on Geographic information systems, Washington, USA, 2004, pp. 2-11.
30.Vogel D. & Balakrishnan D., Interactive public ambient displays: transitioning from implicit to explicit, public to personal, interaction with multiple users, Proceedings of the 17th annual ACM symposium on User interface software and technology, Santa Fe, USA, 2004, pp. 137-146.

三、網路資料

1.劉翰卿，什麼是『Pervasive Computing』 (無所不在的運算)？，取自：http://www.iiiedu.org.tw/knowledge/knowledge20031231_1.htm，2005/10/6。
2.Bill Schilit's Home Page, available at http://seattleweb.intel-research.net/people/schilit/, 2005/10/3.
3.Artificial Intelligence Applications Institute, available at http://www.aiai.ed.ac.uk/, 2005/10/3.
4.MIT Media Laboratory, available at http://www.media.mit.edu/, 2005/10/10.
5.Ambient e-Service Lab NCCU, available at: http://www.aesl.nccu.edu.tw/index.htm, 2005/11/20.
6.W3C World Wide Web, available at http://www.w3.org/, 2006/1/5.
7.The Protégé Ontology Editor and Knowledge Acquisition System, available at http://protege.stanford.edu/, 2006/1/20.
8.Jena Semantics Web Framework, available at http://jena.sourceforge.net/, 2006/3/2.
9.Measuring Search Effectiveness, available athttp://www.hsl.creighton.edu/hsl/Searching/Recall-Precision.html, 2006/3/20.