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研究生:陳泰瑋
研究生(外文):Tai-Wei Chen
論文名稱:設計與實作一可支援情報式網頁搜尋之互動系統
論文名稱(外文):Design and Implementation of an Interactive System for Supporting Informational Web Search
指導教授:鄧維光
指導教授(外文):Wei-Guang Teng
學位類別:碩士
校院名稱:國立成功大學
系所名稱:工程科學系碩博士班
學門:工程學門
學類:綜合工程學類
論文種類:學術論文
論文出版年:2008
畢業學年度:96
語文別:英文
論文頁數:51
中文關鍵詞:網頁搜尋人機互動使用者目的
外文關鍵詞:human-computer interactionuser goalsweb search
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隨著資訊科技的日新月異,充斥在網際網路上的資料量也以驚人的速度大幅增加,為解決資料過載的問題,人們通常使用搜尋引擎以快速地找到所需的資訊,然而由於使用者進行網頁搜尋的目的不一,因此當使用者需要瀏覽搜尋結果時,仍有可能受困於大量資料當中,在本研究中我們設計並開發了一個可支援情報式網頁搜尋的輔助系統,目的即是希望在使用者使用搜尋引擎的過程中,可以類似瀏覽地圖的方式來更精確且快速地瀏覽所需的資訊。進一步而言,我們提出兩個重要的概念,亦即縮小搜尋範圍與重新聚焦,以幫助更有效地定位使用者所需的資訊。經實驗研究之案例探討,我們所提出的方法在實務上可有效地增進現有搜尋引擎的可用性。
As information technologies advance, the data amount gathered on the Internet increases at an incredible rapid speed. To ease the data overloading problem, people commonly use search engines to reach required information in seconds. Nevertheless, depending on different user goals in web search, users occasionally get lost in the large number of search results when trying to explore them. In this work, we propose an interactive scheme to support users to conduct such informational web searches in the similar way of map explorations. Specifically, two main concepts, i.e., refocusing and refinement, are devised to constitute the interactive exploration processes. With a proper design and implementation, case studies utilizing our prototype system show that the proposed approach is feasible in improving usability of current search engines.
Chapter 1 Introduction 1
1.1 Motivation and Overview of the Thesis 1
1.2 Contributions of the Thesis 2
Chapter 2 Literature Survey 3
2.1 User Goals in Web Search 3
2.2 Difficulties Encountered in Current Web Search 6
2.3 Personalized Search with User Profiles 8
2.4 Enhancing Techniques for Web Search 10
2.4.1 Re-Ranking 10
2.4.2 Query Expansion 11
2.4.3 Clustering on Search Results 13
Chapter 3 An Interactive Scheme for Supporting Informational Web Search 17
3.1 System Flows for Interactive Web Search 17
3.2 Schemes of Term Extraction 20
3.2.1 Terms Segmentation 20
3.2.2 Keywords Selection 22
3.3 Identification of User Goals 23
Chapter 4 Empirical Studies 27
4.1 System Implementation 27
4.2 Experimental Results 28
4.2.1 Case 1 29
4.2.2 Case 2 33
4.2.3 Case 3 36
4.2.4 Comparison with Clustering Search Engines 40
4.2.5 Quantitative Analysis 41
Chapter 5 Conclusions and Future Works 44
Bibliography 45
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