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研究生:王翔
研究生(外文):HsiangWang
論文名稱:可供回想並連結新聞事件之視覺建議方法
論文名稱(外文):Associating and Recalling News Events with Visual Suggestions
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:2012
畢業學年度:100
語文別:英文
論文頁數:38
中文關鍵詞:視覺詞袋模型基於圖形內容之影像檢索搜尋建議主題地圖
外文關鍵詞:bag-of-visual-wordscontent-based image retrieval (CBIR)query suggestiontopic map
相關次數:
  • 被引用被引用:0
  • 點閱點閱:156
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  • 下載下載:28
  • 收藏至我的研究室書目清單書目收藏:1
人們的短期記憶容量相當有限,所以對於過往重要的大事件,往往只能埋藏在記憶的深處。而現今人們雖然透過各式媒體接觸到以往數倍之譜的大量資訊,但是比起俯拾即得的各式泛泛網頁,真正能深切感動人心的卻常常只是一張舊照片所帶來的回憶。由於人類的短期記憶有限,大量複雜的資訊不斷增加,導致無法有效的回顧舊有的記憶。有鑑於這個在使用者搜尋並瀏覽網路資料時資料超載所衍生的問題,我們提出藉由提供一些視覺化的建議,來幫助用戶回憶起他們的記憶。不依靠片段的文字資訊,用影像協助使用者找到現在與過去之間的關聯性,成為和過去之間的橋樑。以新聞影像作為回憶的目標,通過比較視覺文字組成的差異,將相似的新聞進一步組合成新聞事件。當用戶在瀏覽當下的新聞時,類似於該新聞影像的新聞事件將從過去的記錄中提出,幫助使用者喚醒過去的記憶。
As more and more information including news articles, personal stories and so on gathered on the Internet, how a user perceives and memorizes every details of what he or she reads is of significant challenge. In view of this information overload problem, recent advances in the research field of information retrieval have resolved most difficulties when a user is able to provide appropriate keywords of his/her search target. Nevertheless, some important events which are etched deeply in one's memory may not be clearly defined as a few keywords or even easily recalled. Thus, we propose in this work to provide some visual suggestions to help users associate and recall their own stories from the memory while reading current news articles. In addition to the usage of fragment text, we propose to extract similarities from news photos. Consequently, resulting suggestions are effective for a user to associate the current news event with previous ones. As such implicit relationships are gradually found, the topic map is then constructed to help a user organize relevant concepts he or she has ever known or learned.
Chapter 1 Introduction 1
1.1 Motivation and Overview 1
1.2 Contributions of This Work 3
Chapter 2 Preliminaries 4
2.1 Image Retrieval Techniques 4
2.1.1 Challenges of Current Image Search Engine 5
2.1.2 Content-based Image Retrieval 6
2.2 Visual Suggestions: Initiative and Passive Ways 9
2.2.1 Visual Query Suggestion 9
2.2.2 Image Browsing Processing 11
2.3 Associating Visual Information 12
Chapter 3 Providing Visual Suggestions in Reading News Events 14
3.1 User Needs in News Browsing 14
3.2 Proposed Scheme for News Visual Suggestion 17
3.2.1 Extracting Visual Information from News 17
3.2.2 Associating News Events 19
Chapter 4 Empirical Studies 24
4.1 Experimental Procedures 24
4.2 Experimental Cases 28
4.3 Experimental Studies 32
Chapter 5 Conclusions and Future Works 34
Bibliography 36

Bibliography
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