臺灣博碩士論文加值系統

近年來由於網路的快速成長，網際網路上的資訊量暴增，使用者若要在網路上搜尋所需的資訊，必須花費大量的時間，因此出現許多搜尋引擎來幫助使用者找尋並整理這些資訊。但是一般搜尋引擎是以條列式的文字來表示搜尋結果，如此的表現方式無法展現搜尋結果之間的關係，使得使用者時常需要逐一地瀏覽每一筆搜尋結果。
為了縮短使用者由搜尋結果中找尋所需資訊所花的時間，本論文提出了一個視覺化介面，稱之為VISE (Visual Interface for Search Engines)。VISE分析搜尋引擎所傳回的結果，得到搜尋結果之間的關係結構圖，並該圖畫出呈現給使用者。VISE利用2D的圖形代替條列式文字來呈現搜尋結果以及它們之間的關係，主要有三項優點：
(1)完整的搜尋結果關係結構可以清楚地呈現在2D的平面上，
避免visual clutter的問題。
(2)使用者可利用圖形直覺地決定瀏覽搜尋結果的順序，減少瀏覽
過程所用的時間。
(3)使用者可輕易於圖形中找到可能討論相同主題而互相連結的搜
尋結果，於其中找到所需的重要資訊。
我們實作VISE雛形系統，將Google搜尋引擎所傳回的搜尋結果經過分析處理，以圖形的方式表示出來，並以查詢兩個字串來呈現應用的實例。
我們也利用實地操作的實驗方式，將VISE與Google搜尋引擎在找尋所需資訊的速度、是否找到重要資訊、搜尋結果的呈現是否清楚以及是否呈現搜尋結果之間關係四個方面作比較。由實驗結果發現，由於VISE利用圖形清楚地呈現搜尋結果以及它們之間的關係，因此加速了使用者瀏覽搜尋結果的速度，並且讓使用者更快地找到所需的重要資訊，而Google缺乏了圖形的輔助，因此在四個比較項目中其平均表現都略遜一籌。由應用實例與評估實驗中我們將可發現VISE的確有以上所提出的優點。
綜合以上所述，我們可以得知VISE的確能減少使用者瀏覽搜尋結果並找到所需資訊的時間，相信能為未來搜尋結果視覺化方法的發展提供幫助，讓使用者能以更快的速度在網路上找到所需要的資訊。

Finding demanded information on the World Wide Web is a time-consuming task.Although some search engines exist to help users query the information,most of them show the search results with pages of scrolled text lists.In this way users may need to check every list entry to assure if it contains the demanded information.The list-based representation conceals the relations among search results and results in encumbrances to searching.
In this thesis a visual interface called VISE (Visual Interface for Search Engines) is proposed.We have also implemented a prototype.VISE has three major advantages:
(1) it clearly shows the complete structure of search
results;
(2) with the assistance of the graphic representation
users can find the more important inforamtion and
the navigation time is thus reduced;
(3) it reveals the relationships of the search results
and help users quickly find the valuable information.
We have compared VISE with Google in four aspects: searching speed,whether users can find the demanded information,
whether the representation of search results is clear,and whether they show the relations among search results.The experimental results show that the average behavior of VISE outperforms in all four aspects with graphic representation.
In conclusion,VISE indeed reduces the time spent in navigating the search results and provides the demanded information more quickly.

1 緒論........................................................1
1.1 簡介...................................................1
1.2 研究動機...............................................3
1.3 研究目標...............................................3
1.4 論文章節介紹...........................................4
2 相關研究....................................................5
2.1 視覺化效果的評估.......................................5
2.2 搜尋結果視覺化技術.....................................6
2.2.1 WebQuery..........................................6
2.2.2 CardVis...........................................8
2.2.3 HyperSpace........................................9
2.3 網頁重要性分析.........................................9
2.4 資訊視覺化技術........................................10
2.4.1 Cone Trees.......................................10
2.4.2 Hyperbolic Browser...............................10
2.5 畫圖演算法............................................12
2.5.1 Four-Pass Algorithm..............................12
2.5.2 CGD..............................................13
2.6 本章總結..............................................13
3 Web搜尋結果視覺化..........................................15
3.1 VISE系統架構..........................................15
3.1.1 Query Preprocessor...............................16
3.1.1.1 分析搜尋結果................................17
3.1.1.2 建構圖形....................................18
3.1.2 圖形操作.........................................19
3.2 畫圖演算法則..........................................21
3.2.1 預備作業.........................................21
3.2.2 族群辨別.........................................21
3.2.3 建立分析樹.......................................22
3.3 本章總結..............................................24
4 系統設計與應用實例.........................................25
4.1 系統環境..............................................25
4.2 實例一................................................25
4.3 實例二................................................28
5 實驗評估與結果.............................................31
5.1 實驗方法..............................................31
5.2 實驗設計..............................................32
5.3 實驗結果..............................................33
5.3.1 實驗一...........................................33
5.3.2 實驗二...........................................36
5.4 使用者意見............................................39
5.5 Web搜尋結果視覺化方法分析.............................39
5.6 本章總結..............................................40
6 未來展望與結論.............................................41
6.1 未來展望..............................................41
6.2 結論..................................................42

[1] Brian Amento, Will Hill, Loren Terveen, Deborah Hix, and
Peter Ju. “An Empirical Evaluation of User Interfaces for
Topic Management of Web Sites”. In Proceedings of the CHI
99 Conference on Human Factors in Computing Systems, pages
552—559,May 1999.
[2] Russell Beale, Rodger J. McNab, and Ian H. Witten.
“Visualizing Sequences of Quries: A New Tool for
Information Retrieval”. In Proceedings of 1997 IEEE Con-
ference on Information Visualization, pages 57—62, August
1997.
[3] Richard Brath. “Metrics for Effective Information
Visualization”. In Proceedings of 1997 IEEE Symposium on
Information Visualization, pages 108—111, October 1997.
[4] Donald Byrd. “A Scrollbar-based Visualization for Document
Navigation”. In Pro-ceedings of the 4th ACM Conference on
Digital Library, pages 122—129, August 1999.
[5] Jeromy Carriere and Rick Kazman. “WebQuery: Searching and
Visualizing the Web through Connectivity”. In Proceedings
of the 6th International World Wide Web Conference, pages
701—711, April 1997.
[6] Hao Chen and Susan Dumais. “Bringing Order to the Web:
Automatically Cate-gorizing Search Results”. In
Proceedings of the CHI 2000 Conference on Human Factors in
Computing Systems, pages 145—152, April 2000.
[7] Peter Eades and Lin Xuemin. “How to Draw a Directed
Graph”. In Proceedings of the IEEE Workshop on Visual
Languages, pages 13—17, October 1989.
[8] Richard H. Fowler, Aruna Kumar, and Jorge L. Williams.
“Visualizing and Browsing WWW Semantic Content”. In
Proceedings of 1996 IEEE First Annual Conference on
Emerging Technologies and Applications in Communications,
pages 110—113, May 1996.
[9] Emden R. Gansner, Eleftherios Koutsofios, Steven C. North,
and Kiem-Phong Vo.“A Technique for Drawing Directed
Graphs”. IEEE Transactions on Software Engi-neering,
19(3):214—230, March 1993.
[10] Chang-Sung Jeong and Alex Pang. “Reconfigurable Disc
Trees for Visualizing Large Hierarchical Information
Space”. In Proceedings of 1998 IEEE Symposium on
Information Visualization, pages 19—25, October 1998.
[11] Brian Johnson and Ben Shneiderman. “Tree-Map: A Space-
Filling Approach to the Visualization of Hierarchical
Information Structures”. In Proceedings of 1991 IEEE
Conference on Visualization, pages 284—291, October 1991.
[12] Can Keskin and Volker Vogelmann. “Effective Visualization
of Hierarchical Graphs with the Cityscape Metaphor”. In
Proceedings of the ACM Workshop on New paradigms in
Information Visualization and Manipulation, pages 52—57,
November 1997.
[13] Hideki Koike and Hirotaka Yoshihara. “Fractal Approaches
for Visualizing Huge Hierarchies”. In Proceedings of 1993
IEEE Symposium on Visual Languages, pages 55—60, August
1993.
[14] John Lamping, Ramana Rao, and Peter Pirolli. “A
Focus+Context Technique Based on Hyperbolic Geometry for
Visualizing Large Hierarchies”. In Proceedings of the
ACM SIGGHI’95 Conference on Human Factors in Computer
Systems, pages 401—408, May 1995.
[15] Jock D. Mackinlay, George G. Robertson, and Stuart K.
Card. “The Perspec-tive Wall: Detail and Context Smoothly
Integrated”. In Proceedings of the ACM SIGCHI’91
Conference on Human Factors in Computing Systems, pages
173—179, April 1991.
[16] Thomas M. Mann. “Visualization of WWW-Search Results”.
In Proceedings of the IEEE 10th International Workshop on
Database and Expert Systems Applications, pages 264—268,
September 1999.
[17] Thomas M. Mann and Harald Reiterer. “Evaluation of
Different Visualizations of Web Search Results”. In
Proceedings of the IEEE 11th International Workshop on
Database and Expert Systems Applications, pages 586—590,
September 2000.
[18] Toshiyuki Masui. “LensBar - Visualization for Browsing
and Filtering Large Lists of Data”. In Proceedings of
1998 IEEE Symposium on Information Visualization, pages
113—120, October 1998.
[19] Carolyn L. McCreary, Richard O. Chapman, and F.-S. Shieh.
“Using Graph Parsing for Automatic Graph Drawing”. IEEE
Transactions on Systems, Man and Cyber-netics, Part A, 28
(5):545—561, September 1998.
[20] D. Scott McCrickard and Colleen M. Kehoe. “Visualizing
Search Results Using SQWID”. In Proceedings of the 6th
International World Wide Web Conference, April 1997.
[21] Sougata Mukherjea and Yoshinori Hara. “Visualizing World-
Wide Web Search En-gine Results”. In Proceedings of the
1999 IEEE International Conference on Information
Visualization, pages 400—405, July 1999.
[22] Tamara Munzner. “H3: Laying Out Large Directed Graphs in
3D Hyperbolic Space”. In Proceedings of 1997 IEEE
Symposium on Information Visualization, pages 2—10,
October 1997.
[23] Lucy Terry Nowell, Robert K. France, Deborah Hix, Lenwood
S. Heath, and Ed-ward A. Fox. “Visualizing Search
Results: Some Alternatives to Query-Document Similarity”.
In Proceedings of the 19 th ACM SIGIR Conference on
Research and Development in Information Retrieval, pages
67—75, August 1996.
[24] George G. Robertson and Jock D. Mackinlay. “The Document
Lens”. In Proceed-ings of the 6th Annual ACM Symposium on
User Interface Software and Technology, pages 101—108,
November 1993.
[25] George G. Robertson, Jock D. Mackinlay, and Stuart K.
Card. “Cone Trees: Ani-mated 3D Visualizations of
Hierarchical Information”. In Proceedings of the ACM
SIGCHI’91 Conference on Human Factors in Computing
Systems, pages 189—194, April 1991.
[26] Manojit Sarkar and Marc H. Brown. “Graphical Fisheye
Views”. Communications of the ACM, 37(12):73—84,
December 1994.