博碩士論文 975202024 詳細資訊




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姓名 張耕輔(Keng-Fu Chang)  查詢紙本館藏   畢業系所 資訊工程學系
論文名稱 網頁內容叢集分類法之設計與實作
(Design and Implementation of Web Content Clustering)
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摘要(中) 仰賴於科技的進步,現今人們獲得資訊的方式已經跟以往大不相同,獲
取資訊的方法已經逐漸的從電腦主機轉移到手持系統上。電腦的瀏覽網頁
資訊的方式並不能完全套用到手持系統上,利用手持系統瀏覽一般為了桌
上型主機而做的網頁並不方便。
為此,本研究基於為了令使用者方便瀏覽一般網頁為出發點,希望能將
網頁內容經過適當的切割、重新賦予標題並進行叢集分類之後能更容易符
合手持系統的顯示及操作,以達到方便瀏覽之目的。
本研究將介紹本實驗室開發的Browsing Rendering System,其運作主要
方法是先透過Mediator 接收使用者瀏覽要求經過網頁內容經由Retriever 做
擷取動作、Extractor 做切割、整合最後利用Cluster 做叢集分類動作,回傳
給Mediator 後Mediator 將網頁叢集結果回傳給使用者。
摘要(英) Nowadays, more and more people are getting used to browsing the Internet
with hand-held devices such as mobile phones or PDAs. However, web pages
most often seen are designed for those devices with large screens such as PCs or
NBs. Thus, these web pages hardly fit into the small devices.
To facilitate wide adoption of hand-held devices for Internet access, we
provide a web content clustering mechanism and devise, a Browsing Rendering
System, so as to display and browse Web content in a better way. In this work, a
web page that is developed for rendering on devices with large screens can be
automatically parsed, re-organized, clustered and displayed on hand-held
devices.
關鍵字(中) ★ 動態網頁
★ 叢集
★ 網頁內容
關鍵字(英) ★ dynamic web page
★ web content
★ clustering
論文目次 摘要 i
ABSTRACT ii
目錄 iii
圖目錄 v
誌謝 vi
第一章、緒論 - 1 -
1.1引言 - 1 -
1.2動機 - 1 -
1.3論文架構 - 2 -
第二章、背景知識介紹 - 4 -
2.1 DOM - 4 -
2.2 HTML - 4 -
2.3 JavaScript - 5 -
2.4 CSS - 5 -
2.5 Dynamic web content - 6 -
2.6 WordNet及WordNet:: Similarity - 7 -
2.7 Longest common substring problem - 8 -
第三章、網頁內容叢集分類法之設計與實作 - 9 -
3.1 系統需求 - 9 -
3.2.1 使用者利用Browsing Rendering System取得網頁資訊之流程說明 - 11 -
3.2.2 使用者在Browsing Rendering System內與網頁互動之流程說明 - 12 -
3.4 主要元件介紹 - 14 -
3.4.1 Mediator - 14 -
3.4.1.1 元件分析 - 14 -
3.4.1.2 元件設計 - 14 -
3.4.2 Parser - 15 -
3.4.2.1 元件分析 - 15 -
3.4.2.2 元件設計 - 16 -
3.4.3 Extractor - 17 -
3.4.3.1 元件分析 - 17 -
3.4.3.2 元件設計 - 18 -
3.4.4 Cluster - 19 -
3.4.4.1 元件分析 - 19 -
3.4.4.2 元件設計 - 19 -
3.5 演算法 - 21 -
3.5.1 Web content segmentation algorithm - 21 -
3.5.2 Clustering Content Blocks Based on Similarity - 24 -
3.5.3 Modified Longest Common Substring - 25 -
第四章、案例分析 - 26 -
4.1 使用案例一:利用Browsing Rendering System觀看npr首頁 - 26 -
4.1.1 使用者執行步驟: - 26 -
4.1.2 系統結果 - 26 -
4.2 使用案例二:使用者開啟npr首頁後,繼續點擊了JavaScript連結 - 29 -
4.2.1 使用者執行步驟 - 29 -
4.2.2 系統結果 - 29 -
第五章、文獻探討 - 31 -
第六章、結論 - 34 -
6.1 貢獻 - 34 -
6.2 未來展望 - 34 -
參考文獻 - 36 -
參考文獻 1. Qinglin Guo, Cunbin Li, “The Research on the Application of Text Clustering and Natural Language Understanding in Automatic Abstracting” , FSKD, Pages: 92-96, IEEE Computer Society Washington, DC, USA, 2007
2. Karane Vieira, “A Fast and Robust Method for Web Page Template Detection and Removal” Conference on Information and Knowledge Management, Pages: 258 – 267, ACM, 2006
3. Stephen J.H. Yang, “A Service Supporting Universal Access to Mobile Internet with Unit of Information-Based Intelligent Content Adaptation” IEEE International Conference on Web Services, 2007
4. Chunying Kang, “DOM-based Web Pages to Determine the Structure of the Similarity Algorithm”, Proceedings of the 3rd international conference on Intelligent information technology application, Pages: 245-248 , IEEE Press Piscataway, NJ, USA, 2009
5. Jing Wang1,Zhijing Liu1, “A Novel Method for the Web page Segmentation And Identification”, ICCET, Pages: 229-231 , IEEE Computer Society Washington, DC, USA, 2009
6. Stephen J.H. Yang, “An Automatic Semantic Segment Detection Service for HTML Documents” Proceedings of the 2008 IEEE International Conference on Services Computing - Volume 1, Pages: 210-217 , IEEE Computer Society Washington, DC, USA, 2008
7. Shian-Hua Lin, Jan-Ming Ho, “Discovering Informative Content Blocks from Web Documents” International Conference on Knowledge Discovery and Data Mining, Pages: 588 - 593 , ACM New York, NY, USA, 2002
8. Vincenzo Loia, Witold Pedrycz, and Sabrina Senatore, “Semantic Web Content Analysis: A Study in Proximity-Based Collaborative Clustering” IEEE TRANSACTIONS ON FUZZY SYSTEMS, VOL. 15, NO. 6, 2007
9. Deng Cai, “VIPS: a Vision-based Page Segmentation Algorithm” Microsoft Research Asia, TechReport, Pages:28, 2003
10. Longzhuang Li, Yonghuai Liu, Abel Obregon, “Visual Segmentation-Based Data Record Extraction from Web Documents”, Information Reuse and Integration, 2007. IRI 2007, Pages: 502 – 507, IEEE, 2007
11. Pyungkwan Ko, Sanggil Kang, Harshit Kumar, “Web Page Dependent Vision Based Segmentation for Web Sites”, Computer and Information Science, 2008. ICIS 08. Pages: 690 – 694, IEEE, 2008
12. Gujjar Vineel, “Web Page DOM Node Characterization and its Application to Page Segmentation”, Internet Multimedia Services Architecture and Applications (IMSAA), Pages: 1 - 6, IEEE, 2009
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14. J. Lee and Y.-Y. Fanjiang, “Modeling Imprecise Requirements with XML,” Information and Software Technology, Vol.45, No.7, pp. 445-460, 2003.
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17. J. Lee and N.-L. Xue, “Analyzing User Requirements by Use Cases, A Goal-Driven Approach,” IEEE Software, Vol.16, No.4, pp. 92- 101, 1999.
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20. W3C.DOM http://www.w3c.org/DOM/
21. Lobo browser http://lobobrowser.org/java-browser.jsp
22. HtmlUnit http://htmlunit.sourceforge.net/
23. WordNet http://wordnet.princeton.edu/wordnet/
24. JAVA WordNet::Similarity http://wn-similarity.sourceforge.net/
25. Wiki http://zh.wikipedia.org/
26. HTML4 http://www.w3.org/TR/REC-html40/
27. JavaScript http://www.w3schools.com/JS/default.asp
28. CSS http://www.w3schools.com/css/default.asp
指導教授 李允中(Jonathan Lee) 審核日期 2010-7-26
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