淡江大學覺生紀念圖書館 (TKU Library)

系統識別號 U0002-2206200612365800
中文論文名稱 以功能性語意註記協助網際網路搜尋之研究
英文論文名稱 Searching the Internet with the Assistance of Functional Semantic Specification
校院名稱 淡江大學
系所名稱(中) 資訊管理學系碩士班
系所名稱(英) Department of Information Management
學年度 94
學期 2
出版年 95
研究生中文姓名 余建昇
研究生英文姓名 Chien-Sheng Yu
學號 693520669
學位類別 碩士
語文別 中文
口試日期 2006-05-20
論文頁數 70頁
口試委員 指導教授-劉艾華
中文關鍵字 功能性語意註記  語意網路  本體論  網頁搜尋 
英文關鍵字 Functional Semantic Annotation  Semantic Web  Ontology  Web Search 
學科別分類 學科別社會科學管理學
中文摘要 近年來,電腦技術快速發展,網路世界的無遠弗屆,資訊量隨之暴增,加上網路便利與不受時空限制的特性,越來越多的人開始藉由它找尋想要的資訊或服務,於是一個優質的搜尋引擎儼然成為資訊需求者不可或缺的工具。目前一般大型的網站,雖然都已陸續提供相關搜尋機制,協助使用者更快速的找到所需資訊。然而,這些搜尋機制大都只能利用所輸入關鍵字比對的方式來擷取列出搜尋的結果。如此一來所搜尋到的資訊大都不是使用者所需的資訊,使用者就必需再以人工的方式去過濾、篩選出想要的資訊,如此的動作將是費時又費力。

但究竟要如何去設計或者提供哪些服務,才能算是一個優良的資訊搜尋引擎? 因此,本研究透過事前的網站分析,依網頁的類型與其所提供的功能加以分類,為網頁增加功能性語意註記。期望搜尋之結果能篩選出與使用者之需求有最近似功能類別之網頁,進而提升搜尋結果的準確性與降低資料找尋之時間。
英文摘要 Recently, the search engines on the WWW has been a necessary tool for many people who’s works are based on the current and correct information. These search portals are trying to serve their customers by providing advanced and convenient mechanisms which are becoming a daily must for gathering information on the Web. These mechanisms help the users to find the suitable web pages in a way that is much more effective than before. However, the key-words based search mechanism usually return too large amount of information for the user to select. The user has to traverse and examine these returned pages one-by-one in order to decide which one is the right web page he needs. Unfortunately, the first page on the list of the search result usually is not the needed one. The user has to “browse through” so many listed pages before he can find a page that is really what he wants.

This problem exists because the key-word based searches only pickup those pages related to the key-words but do not specifying the purpose. That means, what are the actual actions he needs to do with these pages. What can be done towards this problem is to allow the user to specify what they are looking for by pointing out the functional properties of the web pages. For example, if this page contains picture or if this page allow the user to download particular type of information.

This problem points to the necessity of more advanced schemes for the user to be able to specify more clearly the functionalities of the web pages. The Semantic Web proposed by the W3C has been drawing researcher’s attention for its ability of placing meaningful annotations to the web pages. This research attempts to study the possibility of taking the advantage of the Semantic Web and allow the web pages carries information about their functionality.

An ontology concerning the possible functionalities of the web pages has been designed by this research and, based on that, an experiment allowing the user to mark functional annotations into the pages and assisting the web searches has been conducted. It has been shown that adopting this scheme can improve the quality of the web searches by returning more accurate orders of the web pages. It is believed that, after widely accepting this scheme collaboratively, the web searches will be more precise and can save large amount of user’s valuable time.
論文目次 目 錄
第一章、緖論 1
第一節、研究動機 1
第二節、目前對於搜尋結果之改善 2
第三節、研究目標 3
第四節、論文架構 3
第二章、文獻探討 4
第一節、語意網路 4
一、語意網路概述 4
二、語意網路的表示方式 4
三、本體論(Ontology) 8
第二節、資訊擷取技術 9
第三節、網頁資源註記 14
第四節、Creative Commons 15
第五節 協同編輯 21
第三章、研究架構 22
第一節、系統架構 23
一、註記端 24
二、查詢端 24
三、Protégé 25
第二節、網頁之資源類型分析 27
第三節、網頁功能性語意註記之分類 28
第四節、功能性語意註記 32
第五節、產生註記值 34
第六節、功能性語意註記之查詢 38
一、Google搜尋之網頁權重值計算 39
二、本研究查詢之相符性權重值計算 41
第四章、實驗測試 43
第一節、試驗案例 45
第二節、取得試驗樣本 46
第三節、功能性語意註記 47
第四節、搜尋結果之比對 51
第五節、效益分析 53
第五章、結論與未來研究 66
第一節、結論 66
第二節、未來研究 67
參考文獻 68

圖 目 錄

圖1:Swoogle架構圖 10
圖2:協同網頁搜尋架構圖 12
圖3:Creative Commons之Human-Readable Commons Deed 16
圖4:Creative Commons之Lawer-Readable Legal Code-1 17
圖5:Creative Commons之Lawer-Readable Legal Code-2 18
圖6:Creative Commons之Machine-Readable Digital Code 19
圖7:系統架構圖 23
圖8:Protégé軟體畫面 25
圖9:本研究之WebOntology 26
圖10:淡江大學註記頁面 33
圖11:淡江大學網頁之註記值 35
圖12:功能性語意查詢界面 38
圖13:試驗流程圖 44
圖14:Google之「斷背山」搜尋結果 46
圖15:樣本網頁其中之一網頁畫面 48
圖16:為試驗樣本加註相關之註記畫面 49
圖17:經由protégé建構之註記內容 50
圖18:試驗之查尋畫面 51
圖19:功能性語意註記搜尋結果之一 52
圖20:功能性語意註記搜尋結果之二 52
圖21:Google搜尋「斷背山&購物」之搜尋結果 54
圖22:功能性語意搜尋「產品&購物」功能類別之搜尋結果 54
圖23:Google搜尋「斷背山&部落格&文章」之搜尋結果 56
圖24:功能性語意搜尋「文章&部落格」功能類別之搜尋結果 56
圖25:Google搜尋「斷背山&短片&下載」之搜尋結果 58
圖26:功能性語意搜尋「影像」功能類別之搜尋結果 58
圖27:Google與功能性語意搜尋結果之三案例正確率比較 59
圖28:Yahoo奇摩網站分類 63

表 目 錄

表2-1:本研究與Creative Commons之比較 20
表3-1:功能性類別分類表 29
表4-1:功能性語意搜尋與Google搜尋之順位比較 53
表4-2:Yahoo奇摩網站分類與功能性語意分類之比較表 63

參考文獻 [1] Benjamins, V., Fensel, D., Perez, A., Knowledge Management through Ontologies, In Proceedings of Practical Aspects of Knowledge Management, 5, 1998, pp. 1-12.
[2] Carroll, M. W., Creative Commons and the New Intermediaries , Michigan State Law Review, Symposium, 2005
[3] Daconta, M. C., Obrst, L. J., Smith, K. T., The Semantic Web: A Guide to the Future of XML, Web Services and Knowledge Management, Wiley Publish, May 2003.
[4] Despeyroux, T., Practical Semantic Analysis of Web Sites and Documents, WWW2004, May 17–22, 2004, New York, New York, USA.
[5] Dillenbourg, P., Baker, M., Blaye, A., O’Malley, C., The Evolution of Research on Collaborative Learning, In E. Spada & P. Reiman (Eds). Learning in Humans and Machine: Towards an interdisciplinary learning science, Oxford: Elsevier, 1996, pp. 189-211.
[6] Ding, L., Finin, T., Joshi, A., Pan, R., Cost, S. R., Peng, Y., Reddivari, P., Doshi, V., Sachs, J., Swoogle: A Search and Metadata Engine for the Semantic Web, Department of Computer Science and Electronic Engineering University of Maryland Baltimore County, Baltimore MD 21250, USA.
[7] Gruber, T. R., A Translation Approach to Portable Ontology Specifications.
[8] Gulli, A., Ferragina, P., A Personalized Search Engine Based on Web-Snippet Hierarchical Clustering, WWW 2005, May 1014, 2005, Chiba, Japan.
[9] Kalyanpur, A., Parsia, B., Hendler, J., Golbeck, J., SMORE – Semantic Markup, Ontology, and RDF Editor, I.2.4 [Artificial Intelligence]:Knowledge Representation Formalisms and Methods –Representation languages.
[10] Kalyanpur, A., Golbeck, J., Banerjee, J., Hendler, J., OWL: Capturing Semantic Information using a Standardized Web Ontology Language , University of Maryland, College Park.
[11] Kietz, J., Volz, R., Maedche, A., Extracting a Domain-Specific Ontology from a Corporate Intranet, Proceedings of CoNLL-2000 and LLL-2000, pages 167-175, Lisbon, Portugal, 2000.

[12] Lindstrom, B., Creative Commons for Corpus Construction, Uppsala university Department of linguistics and philology.
[13] Muramatsu, J., Transparent Queries: Investigating Users' Mental Models of Search Engines, SIGIR’01, September 9-12, 2001, New Orleans, Louisiana, USA.
[14] Navigli, R., Velardi, P., Learning Domain Ontologies from Document Warehouses and Dedicated Web Sites, Dipartimento di Informatica, Universit`a di Roma “La Sapienza,” Via Salaria, 113 - 00198 Roma, Italia.
[15] Perez, G. A., Ontological engineering: A state of the art. Expert Update, vol. 2, no. 3, Autumn 1999, pp33-43.
[16] Quan,D., Karger, D. R., How to Make a Semantic Web Browser, WWW 2004, May 17–22, 2004, New York, New York, USA.
[17] Ruckhaus, E., Vidal, M. E., An Ontology Language to Describe and Query Web Sources, WIDM’03, November 7–8, 2003, New Orleans, Louisiana, USA.
[18] Shah, U., Finin, T., Joshi, A., Cost, S. R., Mayfield, J., Information Retrieval On The Semantic Web, CIKM’02, November 4–9, 2002, McLean, Virginia, USA.
[19] Smyth, B., Balfe, E., Boydell, O., Bradley, K., Briggs, P., Coyle, M., Freyne, J., A Live-User Evaluation of Collaborative Web Search, Smart Media Institute, Department of Computer Science, University College Dublin, Ireland.
[20] Sure, Y., Studer, R., A Methodology for Ontology-based Knowledge Management, In J. Davies (Ed.), Towards the Semantic Web: Ontology-driven Knowledge Management, Wiley, November 2002.
[21] Craven, P., Google’s PageRank Explained and how to make the most of it, http://www.webworkshop.net/pagerank.html
[22] Creative Commons, http://creativecommons.org/
[23] Creative Commons Taiwan, http://www.creativecommons.org.tw/
[24] Dublin Core Metadata Initiative, http://dublincore.org/
[25] Extensible Markup Language (XML), http://www.w3.org/XML/
[26] OWL Web Ontology Language Guide, W3C Recommendation 10 February 2004, http://www.w3.org/TR/2004/REC-owl-guide-20040210/
[27] Palmer, S. B., The Semantic Web: An Introduction, infomesh.net, September 2001. http://infomesh.net/2001/swintro/
[28] Resource Description Framework (RDF), http://www.w3.org/RDF/
[29] SMORE, Maryland Information and Network Dynamics Lab Semantic Web Agents Project University of Maryland, College Park College Park, Maryland, USA, http://www.mindswap.org/2005/SMORE/
[30] The Power of Metadata, Peer-to-Peer Harnessing the Power of Disruptive Technologies , http://www.openp2p.com/pub/a/p2p/2001/01/18/metadata.html
[31] The Protégé Ontology Editor and Knowledge Acquisition System, http://protege.stanford.edu/
[32] Vivisimo, http://vivisimo.com/html/index
[33] Web 2.0 - Exclusive Demonstration of Clustering from Google, http://www.searchenginelowdown.com/2004/10/web-20-exclusive-demonstration-of.html
[34] Wikipedia, http://www.wikipedia.org
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